Current AI Jobs

Category: AI & Robotics | Site Reliability Engineering | High-Performance Computing

Employment Type: Full-Time

Location: India

Department: AI Infrastructure / Supercomputing

About the Role

Tesla's Supercomputing/AI Infrastructure team works directly with the high-performance computing and machine learning infrastructure that powers Tesla's most demanding ML workloads — from virtual simulations to Autopilot hardware and silicon design. As the scale and complexity of cluster builds continue to grow, the team's focus on automation, monitoring, self-healing, and alerting becomes mission-critical to engineering success across Tesla.

As the scope and impact of Optimus, Full Self-Driving (FSD), and Robotaxi continue to expand, so does the importance of this team's work. As a Site Reliability Engineer, you will be responsible for maintaining and improving the platform that powers Tesla's FSD and Optimus engineering teams — ensuring they have the tools, resources, and infrastructure reliability needed to be productive. Your work will directly enable large-scale neural network training and streamline FSD development.

What You Will Be Doing

AI/ML Cluster Infrastructure Support You will support GPU-based AI/ML cluster infrastructure, with a focus on systems automation, configuration management, and deployment at scale.

Monitoring & Self-Healing Pipelines You will improve monitoring and self-healing pipelines, as well as strengthen the overall security posture of Tesla's AI infrastructure.

Performance Optimisation You will optimise server, storage, and network performance across Tesla's large-scale compute clusters.

Tooling Development You will develop new internal tools using Python, Golang, or Bash/Shell to streamline operations and reduce manual overhead.

Infrastructure as Code You will apply Infrastructure as Code (IaC) best practices to ensure repeatable, scalable, and reliable infrastructure deployments.

On-Call Participation You will participate in a 24x7 on-call rotation, ensuring continuous reliability of critical AI training infrastructure.

Required Qualifications

• Education: Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Physics, or proof of exceptional skills in a related field
• 3+ years of additional equivalent experience, or evidence of exceptional ability related to the position
• Proficiency with Linux fundamentals and performance optimisation
• Experience with Slurm, LSF, and storage management of parallel file systems
• Proficiency in Python, Golang, and/or Bash
• Experience with configuration management software (e.g., Ansible) and systems monitoring & alerting tools (e.g., Prometheus, Grafana, Telegraf, Splunk)
• Experience with containerisation technologies such as Kubernetes
• Experience with high-throughput, low-latency networks, GPU-based computing systems, and/or high-performance storage systems is a plus

About Tesla AI Infrastructure

This team sits at the heart of Tesla's AI ambitions — building and maintaining the supercomputing infrastructure that trains the neural networks behind Full Self-Driving, Optimus, and Robotaxi. As Tesla's compute needs continue to scale rapidly, this team's automation and reliability work becomes increasingly central to the company's AI roadmap.

Category: AI & Robotics | Hardware Engineering | Silicon Design Verification

Employment Type: Full-Time

Location: India

Department: AI Hardware / Silicon Engineering

About the Role

Tesla's AI Hardware team is at the forefront of revolutionising artificial intelligence through cutting-edge hardware innovation. This team designs and develops advanced AI inference chips that accelerate Tesla's machine learning capabilities — including Dojo, Tesla's custom supercomputer built to train massive neural networks on fleet-scale video data. The work of this team powers the neural networks behind Full Self-Driving (FSD) and Tesla's humanoid robot, Optimus.

Within this mission, Tesla's Silicon Engineering team validates DFT (Design-for-Test) features all the way from RTL through silicon bring-up — ensuring test structures function correctly long before a chip ever reaches the tester. As a Staff DFT DV Engineer, you will own the functional verification of all DFT structures at both block and SoC level, delivering pre-silicon testcases that directly enable silicon debug and ATE correlation for Tesla's next-generation AI chips.

This is a senior, high-impact verification role for an engineer who wants to ensure that the test infrastructure behind Tesla's most advanced silicon works flawlessly from day one.

What You Will Be Doing

DFT Feature Verification You will develop SystemVerilog/UVM testbenches to verify core DFT features — including SSN, compressed scan, memory BIST (MBIST), JTAG, and boundary scan — at both block and SoC level.

Top-Level DFT Verification You will verify top-level DFT features such as power-on self-test, clock observation, clock stop, and scan dump, ensuring system-wide test integrity.

DV Regression & Debug You will run design verification regressions, analyse coverage, and triage and debug failures through to closure — maintaining a high-quality, high-coverage verification environment.

RTL Fix Identification & Validation You will identify necessary design fixes and validate corrected DFT RTL, closing the loop between verification findings and design updates.

Pre-Silicon Testcase Delivery You will deliver pre-silicon DV testcases that directly enable silicon bring-up and ATE correlation, bridging the gap between simulation and real silicon.

Post-Silicon ATE Correlation You will own post-silicon ATE test correlation — investigating and root-causing any discrepancies between pre-silicon predictions and actual silicon behaviour.

Agentic AI-Driven Automation You will leverage agentic AI flows to automate regression execution, coverage analysis, and failure triage — accelerating verification cycles across the team.

Required Qualifications

• Education: Degree in Electrical Engineering, Computer Engineering, or a related field — or equivalent practical experience
• 10+ years of DFT design verification (DV) experience at block and SoC level
• Expert-level SystemVerilog and UVM testbench development
• Hands-on verification experience with SSN, compressed scan, MBIST, JTAG, boundary scan, Phy Loopback, and PLL testing
• Demonstrated experience delivering pre-silicon testcases through silicon bring-up and ATE correlation
• Ability to use agentic AI flows to automate DV regression and debug workflows
• Post-silicon debug and ATE correlation experience on server-class SoCs
• Familiarity with formal verification methods for DFT structural checks
• Experience with power-on self-test and clock control verification

About Tesla AI Hardware

The Tesla AI Hardware team is composed of brilliant engineers and visionaries designing custom silicon and optimised architectures that keep Tesla at the forefront of AI-driven automotive and energy solutions — shaping a future where intelligent machines enhance human life. By joining this team, you'll be directly contributing to the verification infrastructure behind the silicon that powers Tesla's most ambitious AI systems, from self-driving cars to humanoid robotics.

Category: AI & Robotics | Hardware Engineering | Silicon Design & Test

Employment Type: Full-Time

Location: India

Department: AI Hardware / Silicon Engineering

About the Role

Tesla's AI Hardware team is at the forefront of revolutionising artificial intelligence through cutting-edge custom silicon. This team designs and develops advanced AI inference chips that accelerate Tesla's machine learning capabilities — including Dojo, Tesla's custom supercomputer built to train massive neural networks on fleet-scale video data. The chips and architectures developed by this team power the neural networks behind Full Self-Driving (FSD) and Tesla's humanoid robot, Optimus.

Within this mission, Tesla's Silicon Engineering team is responsible for delivering production-quality silicon from first tapeout. As a Staff DFT ATPG Engineer, you will own the full structural test lifecycle — from pre-silicon ATPG pattern generation through ATE test program development, DFT timing closure, and OSAT deployment — ensuring world-class test quality and production efficiency at massive scale.

This is a senior, high-ownership role for an engineer who wants to shape how Tesla validates the silicon that powers the future of autonomous driving and robotics.

What You Will Be Doing

ATPG Pattern Generation You will generate production-quality ATPG patterns using Tessent, covering stuck-at, transition delay, path delay, cell-aware, and small delay defect (SDD) fault models.

Coverage Optimisation You will achieve and exceed industry-leading coverage targets — greater than 99% stuck-at and greater than 98% transition coverage — while minimising pattern count to keep ATE test time efficient.

Debug & Coverage Recovery You will debug low-coverage areas including X-state sources, blocking logic, untestable faults, and ATPG abort conditions, driving them to closure.

Hybrid Bonding Test Concepts You will apply your understanding of hybrid bonding test methodologies to advanced packaging and multi-die designs.

Pattern Validation You will perform gate-level pattern simulation to validate the integrity of generated test patterns before silicon deployment.

Hierarchical & Flat ATPG Methodologies You will support both hierarchical and flat ATPG approaches for multi-million gate SoC designs, ensuring scalability across complex chip architectures.

ATE Test Program Development You will architect and develop comprehensive ATE test programs covering ATPG, MBIST, Repair, Functional, DC, and HSIO test domains.

NPI Silicon Bring-Up You will own structural test bring-up for New Product Introduction (NPI) silicon — debugging and root-causing failures through to closure.

OSAT Deployment & Optimisation You will deploy and optimise test programs at OSATs, balancing yield, quality, reliability, and cost at production scale.

Custom Test Method Development You will develop custom test methods tailored to product-specific requirements, and contribute to wafer probe and final test hardware design.

Required Qualifications

• Education: Degree in Electrical Engineering, Computer Engineering, or a related field — or equivalent practical experience
• 10+ years of experience across ATPG, ATE test development, and DFT timing
• Expert-level Tessent proficiency, including TestKompress and MemoryBIST
• Deep knowledge of fault models: stuck-at, transition, path delay, cell-aware, and SDD
• Hands-on ATE test program development and OSAT deployment experience
• SDC constraint development for DFT test modes, with timing closure using Tempus
• Ability to leverage agentic AI flows to automate ATPG and ATE test workflows

About Tesla AI Hardware

The Tesla AI Hardware team is composed of brilliant engineers and visionaries designing custom silicon and optimised architectures that keep Tesla at the forefront of AI-driven automotive and energy solutions — shaping a future where intelligent machines enhance human life. By joining this team, you'll be directly contributing to the silicon that powers Tesla's most ambitious AI systems, from self-driving cars to humanoid robotics.

Category: Artificial Intelligence | Computer Vision | Multimodal LLMs | Agentic AI

Employment Type: Full-Time

Location: Sunnyvale, California, United States

Posted: May 29, 2026

Role Number: 200665673-3956

Applications: Accepted on an ongoing basis

About the Role

Apple's VCV organisation — a centralised applied research and engineering group driving real-time, on-device Computer Vision and Machine Perception across every Apple product — is hiring an AI Engineer for Multimodal Intelligence to join its Human Intelligence team.

This team sits at a rare intersection: deep research meets shipping product. You will work across the full stack of multimodal LLMs — from data collection and curation through modelling, evaluation, and deployment — while directly influencing Apple's sensor and silicon roadmap in partnership with hardware, software, and ML teams.

If you're excited about the frontier of foundation models, multimodal LLMs, and agentic AI systems, and want your research to directly shape the next generation of Apple products, this is your opportunity.

What You Will Be Doing

Multimodal LLM Development You will develop, train, and fine-tune multimodal LLMs spanning image, video, text, and audio modalities — owning the full pipeline from data curation through deployment.

Encoder & Generative Model Design You will design and build video/audio encoders, tokenisers, and generative models that power multimodal understanding and generation across Apple's product ecosystem.

Agentic AI Systems You will design and implement agentic AI systems capable of reliable reasoning — enabling natural, proactive, and personalised human interactions across Apple devices.

End-to-End ML System Architecture You will architect ML systems that transition seamlessly from research prototypes to production-grade technologies at scale, ensuring research breakthroughs actually ship.

Cross-Functional Hardware Collaboration You will collaborate closely with hardware, software, and ML teams to influence sensor and silicon roadmaps, helping deliver pioneering on-device AI experiences.

Code Quality & Engineering Rigour You will critically evaluate and improve ML codebases — ensuring correctness, efficiency, and long-term maintainability across the team's research and production code.

Research Direction & Innovation You will actively contribute to the team's research roadmap, identifying opportunities for innovation in multimodal and agentic AI that directly shape future Apple product features.

Minimum Qualifications

• Education: Master's degree (or equivalent practical experience) in Computer Science, Computer Vision, Machine Learning, or a related technical field
• 3+ years of relevant academic or industry experience in Machine Learning, Computer Vision, or Artificial Intelligence
• Demonstrated deep learning experience with multimodal systems (vision, language, video, etc.)
• Proficiency in Python and a modern deep learning framework such as PyTorch or JAX
• Experience with foundation models (language or multimodal), including training, fine-tuning, and deployment
• Direct experience developing, training, and fine-tuning multimodal LLMs
• Strong foundations in optimisation, probability, and linear algebra as applied to ML and computer vision

Preferred Qualifications

Candidates with the following will be highly competitive:

• PhD (or equivalent practical experience) in Computer Science, Machine Learning, Computer Vision, or a related AI-focused field
• Demonstrated expertise in training and fine-tuning multimodal LLMs at scale, and developing industry-scale agentic products
• Proven technical leadership — architecting complex ML systems and leading projects from conception through product deployment
• Experience applying foundation models to build autonomous or semi-autonomous agents, including planning, task decomposition, and multi-step reasoning
• Strong publication record at top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or COLM
• Experience with large-scale distributed training and model parallelism
• Strong communication skills with the ability to present research findings to both technical and non-technical audiences

Compensation & Benefits

• Base Salary Range: $147,400 – $272,100 USD (dependent on skills, qualifications, experience, and location)
• Eligibility for discretionary restricted stock unit (RSU) awards
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan (ESPP)
• Comprehensive medical and dental coverage
• Retirement benefits
• Discounts on Apple products and access to free Apple services
• Education reimbursement for formal learning related to career advancement at Apple, including tuition support
• Potential eligibility for discretionary bonuses, commission payments, and relocation assistance

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and the terms of the applicable plan or program.

About Apple

The Human Intelligence team operates in one of the most exciting eras of AI — advancing the state of the art in Computer Vision and Machine Learning across every aspect of multimodal LLMs, from data to deployment. Apple is an equal opportunity employer committed to inclusion and diversity, and does not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other legally protected characteristic. Apple participates in E-Verify in locations where required by law, is a drug-free workplace, and will not discriminate or retaliate against applicants who discuss their compensation.

Category: Machine Learning | Generative AI | Model Evaluation | AI Quality Engineering

Employment Type: Full-Time

Weekly Hours: 40 Location: Austin, Texas, United States (3 Work Locations Available)

Posted: June 11, 2026

Role Number: 200667292-0157

About the Role

Apple is hiring a Machine Learning Engineer specialising in ML and GenAI Evaluation to define the quality bar for AI models powering Apple Wallet, Payments, and Commerce. This is not a supporting role — this is the role that decides whether a model ships.

You will own the full evaluation lifecycle for production ML systems, establishing the evaluation criteria, metrics frameworks, adversarial test strategies, and fairness standards that determine when models are truly ready to reach hundreds of millions of users globally. Your technical judgement directly shapes model development priorities and product decisions at Apple's largest scale.

If you believe that how you measure a model is just as important as how you train it — and you hold quality standards that others find uncomfortably high — this role is for you.

What You Will Be Doing

Evaluation Criteria & Quality Metrics Definition You will define the evaluation criteria and quality metrics for ML models powering Wallet features — going far beyond accuracy and F1 to capture precision-recall trade-offs, calibration, fairness dimensions, and task-specific quality standards that genuinely reflect real-world user trust.

Structured Test Set Design You will design and maintain comprehensive test sets covering the full diversity of real-world scenarios — varied document formats, distributions, languages, edge cases, and adversarial inputs — ensuring models are battle-tested before they reach any user.

Robustness & Distribution Shift Testing You will develop evaluation methodologies for robustness testing, covering distribution shift, out-of-distribution generalisation, temporal drift, and aggressor scenarios that expose how models behave under pressure.

Fairness Evaluation Ownership You will own fairness evaluation end-to-end — defining fairness metrics tailored to each Wallet feature, building bias test suites across protected attributes and user populations, measuring disparate performance across subgroups, and enforcing fairness as a hard launch gate with the same rigour as any conventional quality metric.

User Persona–Stratified Benchmarking You will build benchmarks stratified by user persona — reflecting the full breadth of Wallet's global user base across spending patterns, locales, and document types — ensuring no population is underserved by a shipped model.

GenAI & Agentic Model Evaluation You will evaluate generative and agentic model outputs, assessing hallucination rates, faithfulness, and groundedness using LLM-as-a-judge frameworks, human evaluation protocols, and prompt regression testing.

Model Quality Sign-Off You will own the final model quality sign-off process — establishing launch criteria, running final evaluations, and making the definitive call on model readiness before any Wallet feature ships.

Insight Synthesis & Cross-Functional Partnership You will synthesise evaluation results into clear, actionable insights that guide model development priorities and product roadmap decisions. Working closely with ML and Quality Engineering teams, you will identify failure modes early and close the loop between evaluation findings and model improvements.

Evaluation Best Practice Evangelism You will establish and champion evaluation best practices across the Wallet ML team — raising the bar for how models are tested, monitored, and maintained post-launch.

Minimum Qualifications

• Education: MS in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related technical field (strongly preferred) — OR a Bachelor's degree with 7+ years of hands-on experience in ML evaluation, model quality, or applied research
• 5+ years of hands-on ML experience with deep expertise in model evaluation, offline metrics design, and behavioural testing
• Strong track record designing evaluation frameworks for production ML systems — spanning precision-recall trade-offs, calibration, fairness, and task-specific quality dimensions
• Creative ability to translate standard ML metrics (F1, AUC, etc.) into utility and user trust measures
• Proven experience testing for distribution shift, out-of-distribution generalisation, and temporal drift in real-world deployed models
• Demonstrated ability to construct adversarial test suites, aggressor scenarios, and edge-case corpora that surface model failure modes before production
• Experience with structured/semi-structured document understanding, OCR pipelines, or financial data extraction is a strong plus
• Strong Python programming skills with fluency in evaluation tooling, data pipelines, and experiment tracking (MLflow, Weights & Biases, or equivalent)
• Excellent communication skills — able to translate metric results into product-quality narratives for engineering and executive audiences
• Experience owning model quality sign-off in a cross-functional launch process

Preferred Qualifications

Candidates with the following will stand out significantly:

• PhD in Computer Science, Data Science, Statistics, AI/ML, or a related field
• Experience with Bayesian or causal graph-based approaches to data generation
• Experience with causal approaches to fairness evaluation — including counterfactual fairness, causal Shapley values, or structural causal model–based bias auditing
• Experience evaluating models under privacy constraints or on-device inference settings
• Familiarity with confidence calibration techniques and uncertainty quantification
• Background in financial services, fintech, or consumer payment products

About Apple

On the Wallet ML team, rigorous evaluation is not an afterthought — it is the foundation of every model that ships. Apple is an equal opportunity employer committed to inclusion and diversity, and does not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other legally protected characteristic.

Salary information was not disclosed for this role. Compensation will be competitive and consistent with Apple's total rewards package, including equity and comprehensive benefits.

Category: Data Science | Machine Learning | Generative AI | Model Quality & Observability

Employment Type: Full-Time

Weekly Hours: 40

Location: Austin, Texas, United States (3 Work Locations Available)

Posted: June 11, 2026

Role Number: 200667346-0157

About the Role

Apple is seeking a Data Scientist specialising in AI/ML Model Quality to join the team responsible for the data integrity of ML and Generative AI systems powering Apple Wallet, Payments, and Commerce. This is a foundational role — because at Apple, exceptional models begin with exceptional data.

You will own the health of the data ecosystem that sits beneath every ML and GenAI feature reaching hundreds of millions of users worldwide. From building intelligent validation frameworks and defining observability metrics to leading telemetry analysis across GenAI workflows, your work ensures that every model Apple builds is trained, evaluated, and deployed on data the entire organisation can trust.

This role sits at the precise intersection of statistical rigour and production systems — uniquely positioned between ML Engineering, Data Engineering, Privacy, and Legal teams.

What You Will Be Doing

Ground-Truth Dataset Curation & Validation You will curate, analyse, and maintain gold-standard ground-truth datasets used for model evaluation and continuous validation across both conventional ML and GenAI systems — ensuring every benchmark Apple's models are measured against is trustworthy and up-to-date.

Bias Auditing & Fairness Analysis Before any model ships, you will audit training data for systemic bias and fairness gaps. You will then establish ongoing analytical checks that catch bias introduced by data drift over time — keeping Apple's financial AI features equitable and compliant.

Data Quality Metrics Definition & Reporting You will define, track, and report key data quality metrics — including completeness, accuracy, timeliness, and validity — presenting findings clearly to both engineering teams and senior leadership.

Automated Data Quality Rules & CI/CD Integration Working alongside Data Engineering, you will design and define automated data quality rules and threshold checks, ensuring these are embedded directly into model development pipelines and CI/CD workflows.

ML Observability & Production Monitoring You will define and own ML observability metrics covering model performance, output distributions, training-serving skew, feature drift, and silent degradation — translating raw production signals into actionable guidance for engineering and product teams.

Observability Dashboards & Reporting You will design and build observability dashboards and reporting workflows that give stakeholders a consistent, real-time view of model health across both ML and GenAI systems.

GenAI Telemetry Analysis You will define and analyse telemetry across GenAI workflows — tracking quality signals such as output coherence, latency, task completion rates, and regression patterns — and translate those findings into concrete recommendations for model and data teams.

Failure Mode Identification Through systematic telemetry analysis, you will identify degradation patterns and domain-specific failure modes in GenAI systems before they impact users.

Minimum Qualifications

• Education: Bachelor's degree with exceptional hands-on ML/AI model quality or applied research experience — or an MS or PhD in Machine Learning, Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field (strongly preferred)
• 3+ years of experience in data science or a closely related analytical role, with a strong focus on data quality, model evaluation, or ML observability in production environments
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL for complex data analysis, metric creation, and validation
• Experience querying and analysing large-scale datasets using distributed computing frameworks such as PySpark, Spark, or distributed SQL
• Solid understanding of statistical methods — hypothesis testing, distribution analysis, data drift detection, and statistical process control
• Demonstrated experience defining and tracking ML model health metrics in production — including model performance monitoring, feature drift detection, and observability instrumentation
• Familiarity with GenAI or LLM systems, including common quality failure modes, output evaluation approaches, and telemetry instrumentation
• Strong communication skills — able to translate complex data quality findings and model health risks into clear, actionable insights for both engineering and non-technical stakeholders

Preferred Qualifications

Candidates with the following experience will be strongly competitive:

• Experience with data visualisation and dashboarding tools such as Tableau, Apache Superset, or Databricks to present complex ML telemetry
• Familiarity with LLM evaluation frameworks such as LangSmith, or techniques like LLM-as-a-judge
• Experience with Bayesian or causal graph-based approaches to synthetic data generation
• Familiarity with confidence calibration techniques and uncertainty quantification
• Experience with ML monitoring or observability platforms such as MLflow, Weights & Biases, or equivalent
• Experience working with privacy-constrained data or under regulatory compliance frameworks such as GDPR or DMA
• Background in financial services, fintech, or consumer payment products

About Apple

At Apple, data quality is not a checkbox — it is the bedrock of every AI-powered product that reaches users at scale. This team defines what exceptional data quality looks like for machine learning across Wallet, Payments, and Commerce. Apple is an equal opportunity employer committed to inclusion and diversity, and does not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other legally protected characteristic.

Salary information was not disclosed for this role. Compensation will be competitive and consistent with Apple's total rewards package, including equity and comprehensive benefits.

Category: Machine Learning | Generative AI | Deep Learning Infrastructure

Employment Type: Full-Time

Location: Cupertino, California, United States (2 Work Locations Available)

Posted: June 5, 2026

Role Number: 200651112-0836

Applications: Accepted on an ongoing basis

About the Role

Apple's Intelligence System Experience (ISE) team is hiring a Senior Machine Learning Engineer to help build the next generation of large-scale deep learning infrastructure powering Apple Intelligence. This is a rare opportunity to work at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalised Intelligent Experiences — all within one of the world's most impactful technology companies.

Your work will be deployed across high-impact Apple Intelligence products spanning both on-device and server environments, and you will have genuine opportunities to open-source your contributions to the global ML community. If you are a PyTorch-focused ML systems expert who thrives on pushing the boundaries of training and inference performance, this role was built for you.

What You Will Be Doing

As a Senior ML Engineer on the ISE team, you will operate at the systems level — designing, building, and optimising the core platform that makes Apple's AI-driven experiences possible at scale.

Core ML Platform Development You will develop foundational components for Apple's centralised, scalable ML platform — building the infrastructure that powers training and inference for Apple Intelligence products across teams.

Training & Inference Acceleration You will push the limits of existing training technologies, create novel techniques to overcome system constraints, and drive improvements in both training speed and inference performance.

Software–Hardware Co-Design Leveraging a deep understanding of hardware-software co-design principles, you will optimise ML workloads to extract maximum efficiency from both on-device silicon and large-scale server infrastructure.

PyTorch Systems Engineering You will work deeply within the PyTorch software stack — maintaining and advancing state-of-the-art ML frameworks, contributing to system-level optimisations, and driving efficiency improvements from small on-device models all the way to massive foundation models.

Open Source Contribution You will be actively encouraged to open-source your contributions — giving back to the broader ML research and engineering community while strengthening Apple's presence in the ecosystem.

Cross-Team Collaboration You will partner closely with teams across Apple who are building Apple Intelligence products, ensuring the ML platform you develop translates directly into world-class user experiences.

Minimum Qualifications

• Education: PhD or Master's degree in Computer Science, or equivalent industry experience, with 3+ years of hands-on experience in the AI/ML field
• Strong Python programming skills
• Solid understanding of software–hardware co-design principles and algorithms
• Deep working knowledge of the PyTorch software stack, with experience maintaining production-grade ML frameworks
• Strong understanding of LLM architectures and their core building blocks

Preferred Qualifications

Candidates with the following will be strongly competitive:

• Experience working on AI/ML-optimised runtime stacks
• Familiarity with parallelisation algorithms for large model training
• Up-to-date knowledge of recent developments in foundation model architectures
• Experience with parallel training libraries such as PyTorch Distributed (torch.distributed), DeepSpeed, or FairScale
• Experience building ML models optimised for on-device inference
• Publication record at top-tier ML conferences such as MLSys, NeurIPS, ICML, or similar

Compensation & Benefits

• Base Salary Range: $181,100 – $318,400 USD (dependent on skills, qualifications, experience, and location)
• Eligibility for discretionary restricted stock unit (RSU) awards
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan (ESPP)
• Comprehensive medical and dental coverage
• Retirement benefits
• Discounts on Apple products and access to free Apple services
• Education reimbursement for formal learning related to career advancement at Apple, including tuition support
• Potential eligibility for discretionary bonuses, commission payments, and relocation assistance

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and the terms of the applicable plan or program.

About Apple

The ISE team is a multidisciplinary group of highly skilled, impact-focused engineers operating at the frontier of AI. Apple offers a respectful work environment, flexible responsibilities, access to world-class technical experts, and meaningful growth opportunities. Apple is an equal opportunity employer committed to inclusion and diversity, and does not discriminate on the basis of race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other legally protected characteristic. Apple believes accessibility is a fundamental human right — reflected across its culture, benefits, and tools.

Category: Artificial Intelligence | Quality Assurance | Machine Learning

Employment Type: Full-Time

Location: Beijing, China

Posted: May 27, 2026

Role Number: 200665346-0351

About the Role

Apple is looking for a talented and driven AI Quality Assurance Engineer to join its engineering team in Beijing. This is a technically demanding, multi-disciplinary role designed for someone who thrives at the intersection of quality engineering, live system operations, and applied AI. You will serve as a critical technical backbone for some of Apple's most advanced software ecosystems — ensuring that millions of users experience flawless, resilient software every single day.

If you love chasing down elusive bugs across complex distributed systems, have a working understanding of Large Language Models (LLMs), and can stay sharp and decisive during live production incidents, Apple wants to hear from you.

What You Will Be Doing

As an AI QA Engineer at Apple, your responsibilities span the full quality and operations lifecycle — from proactive testing strategy design all the way through to live incident resolution.

Proactive Quality Assurance & Testing You will design, automate, and execute rigorous testing strategies using strong QA methodologies. Your goal is to surface hidden system anomalies, functional bugs, and quality degradation in complex software workflows before they ever reach end users.

Deep Root-Cause Analysis & Triaging You will trace issues across multi-tiered architectures — from backend services down to client-side logs — pinpointing the precise origin of complex defects across the entire technology stack.

AI-Empowered Development & Tooling Leveraging your knowledge of generative AI and LLMs, you will build internal tools, automation scripts, and frameworks that integrate LLM capabilities into operational workflows — boosting testing efficiency, log analysis, and daily engineering productivity.

Live Operations & Incident Response You will act as a first line of defence during technical escalations — monitoring service health, investigating live system anomalies, managing time-sensitive issues, and driving production incidents to full resolution.

Infrastructure & Automation Optimisation You will maintain, optimise, and enhance existing QA automation frameworks, CI/CD pipelines, and monitoring tooling to continuously scale and strengthen the team's testing posture.

Cross-Functional Collaboration Working alongside internal engineering teams, machine learning teams, and third-party partners, you will lead joint debugging efforts and translate complex technical findings into clear, actionable, and permanent systemic fixes.

Minimum Qualifications

• Education: BS or MS in Computer Science, Software Engineering, Information Systems, or equivalent practical experience
• Strong foundational knowledge in Computer Science, spanning Quality Assurance, Software Troubleshooting, and System Operations
• Proven ability to test and debug complex distributed systems, isolating bugs across both backend services and client applications
• Fundamental understanding of generative AI concepts including LLMs, with practical ability to use AI models via APIs for automation, scripting, and process optimisation
• Demonstrated experience in QA automation, live incident response, and driving technical escalations to resolution in fast-paced environments
• Practical experience reading and interpreting client-side logs (iOS/macOS environments) for effective end-to-end triaging
• Excellent analytical, root-cause analysis, and communication skills — able to translate complex system logs into clear insights for both technical and non-technical stakeholders

Preferred Qualifications

Candidates with the following will be strongly considered:

• Proficiency in scripting and automation languages such as Python or Bash for building and optimising testing tools, operational workflows, or LLM-based utility scripts
• Familiarity with building lightweight AI applications, including agentic coding frameworks or similar productivity tooling
• Experience with software compliance, technical audits, or regional operational rollouts
• A proactive, hands-on mindset with a passion for building scalable and robust quality processes
• High adaptability and composure during critical software incidents

About Apple

At Apple, quality is not a department — it is a culture. Apple is an equal opportunity employer committed to inclusion, diversity, and accessibility as a fundamental human right. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Every perspective matters, and Apple actively fosters an environment where you can build a career where you truly belong.

Category: Artificial Intelligence | Machine Learning | Enterprise Software

Employment Type: Full-Time

Location: Santa Clara, CA / US Remote

Posted: June 10, 2026

Application Deadline: June 14, 2026

About the Role

NVIDIA is hiring a Solutions Architect specialising in Agentic AI to join its NVIDIA AI Enterprise (NVAIE) Solutions Architecture Segment Team. This is a high-impact engineering and customer-facing role at the frontier of generative AI, where you will design, prototype, and deploy intelligent AI agent systems for large enterprise clients.

The Agentic AI team focuses on solving real-world enterprise challenges using cutting-edge techniques — from Test Time Compute and Reinforcement Learning to inference optimisation and model fine-tuning. If you are passionate about building production-ready AI agents that actually work at scale, this role puts you at the centre of that mission.

What You Will Be Doing

As a Solutions Architect on the Agentic AI team, your day-to-day will involve architecting and building enterprise-grade AI agent applications using the latest agentic frameworks. You will integrate enterprise data sources — text, code, and images — into meaningful, results-driven agentic workflows.

Key responsibilities include:

• Designing and developing multi-agent systems using frameworks such as LangGraph, LlamaIndex, and CrewAI
• Building solutions like deep research assistants, multi-modal dialogue systems, and task-specific enterprise agents
• Engaging directly with customer engineering teams to deliver first-time implementations of NVIDIA AI Enterprise software
• Providing hands-on feedback to NVIDIA's product teams to improve software offerings based on real deployment experience
• Educating vertical teams and building internal knowledge communities around NVIDIA AI software products
• Staying ahead of advancements in LLM reasoning, agentic orchestration, and AI infrastructure

Required Qualifications

• Education: BS, MS, or Ph.D. in Engineering, Mathematics, Physics, Computer Science, Data Science, or a related field — or equivalent hands-on experience
• Experience: 5+ years with a demonstrated track record in Deep Learning and Machine Learning
• Programming: Strong software engineering skills in Python, C/C++, and Linux
• Frameworks: Practical experience with deep learning frameworks such as TensorFlow or PyTorch
• AI Agents: Hands-on experience building advanced multi-agent systems using LangGraph, LlamaIndex, or CrewAI
• GPU Expertise: Demonstrated experience working with GPU-accelerated computing
• Communication: Excellent written and verbal communication skills; comfortable collaborating with both executive stakeholders and engineering teams
• Ability to manage multiple priorities in a fast-moving, dynamic environment

Preferred / Standout Qualifications

Candidates who possess the following will stand out:

• Experience building evaluation harnesses, success metrics, automated testing pipelines, and guardrail frameworks for safe and reliable agentic AI workflows
• Expertise in fine-tuning and optimising reasoning-focused LLMs and SLMs, including prompt engineering, quantisation, and benchmarking
• Production deployment experience using Kubernetes, OpenShift, CI/CD automation, and secure cloud-native infrastructure

Compensation & Benefits

• Level 3 Base Salary Range: $152,000 – $241,500 USD
• Level 4 Base Salary Range: $184,000 – $287,500 USD

Final base salary is determined by your location, experience, and internal pay equity. In addition to base salary, this role is eligible for equity (RSUs) and a comprehensive benefits package.

Why NVIDIA

NVIDIA is a global leader in accelerated computing and AI infrastructure. The NVAIE team works at the bleeding edge of enterprise AI adoption — not theoretical research, but real production deployments that change how businesses operate. You will have access to NVIDIA's latest hardware, software stack, and research, while making a direct, measurable impact on the AI industry.

NVIDIA is an equal opportunity employer and is committed to building an inclusive workplace. The company does not discriminate on the basis of race, religion, colour, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

Note: NVIDIA uses AI-assisted tools in its recruiting processes.

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Location: London, Hursley, Leicester, Manchester, United Kingdom
Job Type: Full-Time | Professional
Company: IBM Consulting UK FutureNow
Required Education: None
Preferred Education: Bachelor's Degree

Job Overview

At IBM Consulting, you'll build your career at the forefront of Artificial Intelligence, Hybrid Cloud, and Digital Transformation, working alongside leading organizations across both public and private sectors.

As a Data Scientist – AI, you will play a key role in designing, developing, and delivering advanced AI solutions that solve complex business challenges and create measurable value for clients. This is an exciting opportunity to work with cutting-edge technologies including Foundation Models, Large Language Models (LLMs), Machine Learning, and Generative AI while contributing to high-profile programs across multiple industries.

We are seeking a highly experienced professional with deep expertise in AI, machine learning, cloud technologies, and data science who can lead projects, mentor teams, and shape AI strategies for enterprise clients.

Key Responsibilities

AI Solution Architecture & Delivery

• Architect, design, and deliver advanced AI solutions using modern artificial intelligence techniques.
• Develop and deploy solutions leveraging:
  • Foundation Models
  • Large Language Models (LLMs)
  • Machine Learning
  • Cognitive Computing Technologies
• Lead the complete AI solution lifecycle from concept and design through deployment, evaluation, and optimization.
• Ensure AI solutions align with business goals and deliver measurable outcomes.

AI Strategy & Innovation

• Define and implement AI and cognitive computing strategies aligned with organizational objectives.
• Identify opportunities to leverage emerging AI technologies to solve complex business challenges.
• Drive innovation through the adoption of modern AI methodologies and best practices.

Leadership & Team Development

• Mentor and support mid-level Data Scientists and AI practitioners.
• Promote knowledge sharing, technical excellence, and continuous learning.
• Provide technical guidance across project teams and AI initiatives.

Client & Stakeholder Engagement

• Build strong relationships with clients and key stakeholders.
• Communicate technical concepts clearly to both technical and non-technical audiences.
• Ensure successful delivery through effective collaboration and stakeholder management.
• Support strategic decision-making through AI expertise and advisory services.

Required Qualifications

Education

• No formal education requirement.
• Bachelor's Degree preferred.

Required Technical & Professional Expertise

Artificial Intelligence & Machine Learning

• Extensive experience in:
  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Data Science
  • Foundation Models
  • Large Language Models (LLMs)
• Proven ability to architect and deliver enterprise-scale AI solutions.

Programming & AI Frameworks

• Expert-level Python programming skills.
• Strong experience with AI and Machine Learning frameworks, including:
  • TensorFlow
  • PyTorch
  • Keras

Cloud Platforms

• Deep understanding of cloud technologies and services, including:
  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform (GCP)

Enterprise AI Delivery

• Demonstrated success delivering complex AI solutions in professional environments.
• Strong understanding of AI solution design, deployment, evaluation, and optimization.

Leadership & Communication

• Exceptional communication and stakeholder management skills.
• Strong leadership and mentoring capabilities.
• Advanced problem-solving and analytical thinking skills.

Security Clearance Requirements

This role is subject to pre-employment screening in accordance with the UK Government's:

Baseline Personnel Security Standard (BPSS)

Additional National Security Vetting (NSV) requirements may apply, including eligibility for:

• Security Check (SC)
• Developed Vetting (DV)

Candidates must be able to meet applicable security and vetting requirements.

Preferred Qualifications

Generative AI & Deep Learning

• Experience working with:
  • Generative AI models
  • Deep Learning architectures
  • Advanced neural network frameworks

Front-End & UI Technologies

Familiarity with modern web and UI frameworks, including:

• Backbone.js
• AngularJS
• React.js
• Ember.js
• Bootstrap
• jQuery

Databases & Data Platforms

Experience with:

Relational Databases

• SQL
• PostgreSQL
• DB2

NoSQL Databases

• MongoDB

Operating Systems

Working knowledge of:

• Linux
• Windows
• iOS
• Android

Why Join IBM Consulting UK FutureNow?

IBM Consulting UK FutureNow provides opportunities to work on transformative AI and Hybrid Cloud projects while accelerating your career growth through continuous learning and hands-on experience.

What You'll Gain

• Exposure to cutting-edge AI, cloud, and data technologies.
• Experience delivering solutions for leading public and private sector organizations.
• Access to industry-leading professionals and technical experts.
• Opportunities for long-term career progression and skills development.
• A flexible and inclusive work environment that values innovation and individuality.

Benefits & Perks

IBM offers a comprehensive benefits package designed to support your professional and personal well-being.

Work-Life Balance

• Flexible working arrangements
• Sabbatical programs
• Paid paternity leave
• Maternity leave
• Innovative maternity returners scheme

Healthcare Benefits

• Private medical insurance
• Dental cover
• Optical cover
• Employee Assistance Program (EAP)

Financial Benefits

• Group pension plan via salary sacrifice
• Life assurance

Paid Time Off

• 25 days annual leave
• Public holidays

Employee Discounts

• Online shopping discounts
• Additional employee benefits and support programs

About IBM Consulting

IBM Consulting is IBM's global consulting and professional services organization, helping businesses transform through technology, strategy, and innovation.

With deep expertise across industries and emerging technologies, IBM Consulting delivers market-leading solutions in Artificial Intelligence, Hybrid Cloud, Digital Transformation, and Business Operations.

Our teams collaborate with some of the world's most innovative organizations to accelerate business outcomes and unlock new opportunities.

About IBM

Since 1911, IBM has been a global leader in innovation, pioneering advancements in:

• Artificial Intelligence
• Hybrid Cloud
• Quantum Computing
• Blockchain
• Enterprise Technology Solutions

IBM remains committed to responsible technology innovation that improves businesses, communities, and society worldwide.

Equal Opportunity Employer

IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, citizenship status, immigration status, or any other characteristic protected under applicable law.

Flexible Working

IBM encourages employees to bring their whole selves to work and supports flexible working arrangements wherever business requirements permit. Candidates interested in flexible working options are encouraged to discuss available arrangements with the recruitment team.

*Check Information From official Website. This is AI content.

Location: Denver, Colorado | Texas | New York | Oregon | Utah | California, United States
Job Type: Full-Time | Professional
Education Required: Bachelor's Degree
Preferred Education: Bachelor's Degree
Company: IBM Consulting

Job Overview

IBM Consulting is seeking a talented Consultant – AI Engineer to join our growing Data & AI practice. In this role, you will specialize in building, enhancing, and optimizing Snowflake-based Data and AI platforms that enable clients to accelerate their data modernization and artificial intelligence initiatives.

As a Data Engineer focused on Snowflake technologies, you will play a critical role in implementing enterprise-scale data and AI use cases, leveraging expertise in Snowflake, SAP, cloud computing, and data engineering to deliver scalable, high-performance solutions.

This position offers the opportunity to work with leading organizations across industries while helping shape their hybrid cloud and AI transformation journeys.

Key Responsibilities

Snowflake Data & AI Platform Development

• Build, enhance, and maintain Snowflake platforms supporting enterprise Data and AI initiatives.
• Implement Data and AI use cases on Snowflake environments with a focus on scalability, performance, and reliability.
• Ensure seamless integration between Snowflake platforms and enterprise systems.
• Support data modernization initiatives through cloud-based data platform solutions.

Data Engineering & Solution Delivery

• Apply data engineering principles and best practices to deliver high-quality technical solutions.
• Design and implement data pipelines that support analytics and AI workloads.
• Optimize Snowflake environments to improve performance and operational efficiency.
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions.

Cloud & AI Integration

• Leverage cloud computing technologies to support Data and AI platform implementations.
• Integrate Snowflake platforms with cloud-native services and enterprise applications.
• Support deployment and optimization of AI-driven data solutions.
• Ensure secure, scalable, and maintainable cloud-based architectures.

Technical Consulting

• Provide technical expertise and recommendations to clients.
• Contribute to solution design, implementation, and optimization initiatives.
• Work collaboratively with cross-functional teams across Data, AI, Cloud, and SAP domains.
• Deliver solutions aligned with client business objectives and technology strategies.

Required Qualifications

Education

• Bachelor's Degree (Required)
• Bachelor's Degree (Preferred)

Required Technical & Professional Expertise

SAP & Enterprise Data Expertise

• Deep expertise in SAP technologies.
• Strong knowledge of SAP AI capabilities and integrations.

Snowflake Platform Expertise

• Experience building and enhancing Snowflake platforms.
• Proven ability to implement Data and AI use cases on Snowflake environments.
• Knowledge of Snowflake architecture, optimization, and performance management.

Data Engineering

• Strong understanding of data engineering principles and best practices.
• Experience designing and implementing scalable data solutions.
• Ability to deliver high-quality data and AI platform implementations.

Cloud Computing

• Experience working with cloud computing concepts and technologies.
• Understanding of cloud-native architectures and services.
• Ability to integrate cloud platforms with Snowflake environments.

Solution Implementation

• Experience implementing enterprise Data and AI use cases.
• Ability to ensure seamless integration and optimal performance.
• Proven track record of delivering technical solutions that address client business requirements.

Preferred Qualifications

Cloud Integration

• Experience integrating cloud technologies with Snowflake platforms.
• Understanding of hybrid cloud and enterprise cloud architectures.

Advanced Data Engineering

• Advanced experience applying data engineering methodologies within Snowflake ecosystems.
• Ability to design and optimize complex data workflows supporting AI and analytics initiatives.

Solution Optimization

• Experience optimizing Snowflake-based solutions for performance, scalability, and operational efficiency.
• Ability to improve Data and AI platform effectiveness through technical enhancements and best practices.

Why Join IBM Consulting?

IBM Consulting partners with organizations worldwide to transform businesses through innovative technologies, including Artificial Intelligence, Data Platforms, Cloud Computing, and Hybrid Cloud solutions.

As part of IBM Consulting, you will:

• Work on enterprise-scale Data and AI transformation projects.
• Collaborate with industry-leading professionals and technology experts.
• Gain exposure to cutting-edge Snowflake, SAP, AI, and cloud technologies.
• Build a long-term career within a global technology and consulting leader.
• Access continuous learning and professional development opportunities.

Employee Benefits

Eligible employees may have access to IBM's comprehensive benefits package, including:

Healthcare Benefits

• Medical Coverage
• Prescription Drug Coverage
• Dental Insurance
• Vision Insurance
• Mental Health and Well-being Programs

Financial Benefits

• 401(k) Program
• Cash Balance Pension Plan
• IBM Employee Stock Purchase Plan (ESPP)
• Life Insurance
• Financial Counseling
• Short-Term Disability Coverage
• Long-Term Disability Coverage
• Performance-Based Incentive Programs

Paid Time Off

• 12 Paid Holidays
• Minimum 56 Hours of Sick Leave
• 120 Hours of Vacation
• 12 Weeks of Parental Bonding Leave
• Paid Care Leave Programs
• Paid Family Leave Benefits (where applicable)

Learning & Development

• AI-powered personalized learning platform
• Industry-recognized certification opportunities
• Continuous technical and professional development resources

Diversity & Inclusion

• Employee Resource Groups
• Volunteer and Community Programs
• Inclusive workplace culture
• Employee discounts on products, services, and experiences

Important Employment Information

Visa Sponsorship

IBM will not provide visa sponsorship for this position now or in the future. Applicants must be authorized to work in the United States without requiring current or future visa sponsorship.

Compensation

Compensation will vary based on:

• Relevant skills and qualifications
• Professional experience
• Geographic location
• Employment classification

Compensation, benefits, and paid time off may be adjusted for part-time employees and individuals joining during the calendar year.

Background Consideration

IBM considers qualified applicants with criminal histories in accordance with applicable laws.

About IBM Consulting

IBM Consulting is IBM's consulting and global professional services organization, helping clients accelerate business transformation through strategy, technology, and operations services.

With expertise across industries and emerging technologies, IBM Consulting delivers innovative solutions that help organizations modernize, innovate, and achieve measurable business outcomes.

About IBM

Since 1911, IBM has been a global technology leader driving innovation in Artificial Intelligence, Hybrid Cloud, Quantum Computing, Blockchain, and Enterprise Technology Solutions.

IBM remains committed to responsible innovation and creating technology that benefits businesses, communities, and society worldwide.

Equal Opportunity Employer

IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, citizenship status, immigration status, or any other legally protected characteristic.

Location: Oslo, Norway
Job Type: Full-Time | Professional
Industry: Defense & Intelligence | Artificial Intelligence | Consulting
Education Required: Bachelor's Degree
Company: IBM Consulting

Job Overview

Are you passionate about building AI solutions that strengthen national security and enhance defense decision-making capabilities?

IBM Consulting is seeking an experienced AI Engineer – Enterprise AI for Defense Sector to join our growing Defense & Intelligence practice in Norway. This role offers the opportunity to work on mission-critical projects supporting NATO and Norway's digital defense capabilities, where precision, security, resilience, and speed are essential.

As an AI Engineer, you will develop and integrate advanced AI solutions into secure operational environments, helping defense organizations gain faster, more reliable insights and decision support capabilities. You will collaborate with architects, analysts, and operational teams to deliver scalable AI systems that directly contribute to national preparedness and security.

Key Responsibilities

AI Solution Development & Integration

• Implement and integrate AI-driven solutions into secure, mission-critical environments.
• Develop and deploy Retrieval-Augmented Generation (RAG) pipelines.
• Optimize Large Language Models (LLMs) for:
  • Situational awareness
  • Decision support
  • Operational analysis
• Design and build APIs, integration layers, and event-driven architectures that support real-time information exchange.
• Create scalable AI services that support defense and intelligence operations.

Platform Engineering & Operations

• Ensure high availability, reliability, and operational excellence of AI systems.
• Monitor and optimize system performance and observability.
• Implement compliance controls aligned with strict security and regulatory requirements.
• Support deployment and lifecycle management of AI platforms and services.

Cross-Functional Collaboration

• Work closely with solution architects, analysts, operators, and engineering teams.
• Participate in defense-related AI initiatives and enterprise modernization programs.
• Contribute to secure and responsible AI implementation practices.
• Bridge advanced AI technologies with highly regulated operational environments.

Required Qualifications

Education

• Bachelor's Degree

Required Technical & Professional Expertise

AI & Machine Learning Platforms

Experience with one or more of the following AI platforms:

• Azure OpenAI
• AWS Bedrock
• Google Vertex AI
• IBM Watsonx
• OpenShift AI

Generative AI & LLM Technologies

• Strong understanding of Large Language Models (LLMs).
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
• Experience working with vector databases and semantic search solutions.

Programming & AI Frameworks

• Strong proficiency in Python.
• Hands-on experience with frameworks such as:
  • LangChain
  • LlamaIndex
  • Semantic Kernel

Cloud-Native & Platform Engineering

• API development and integration.
• Microservices architecture.
• Containerization technologies:
  • Docker
  • Kubernetes
  • OpenShift

DevOps & Infrastructure

• CI/CD pipeline implementation and management.
• Infrastructure as Code (IaC).
• Monitoring and observability solutions.
• Secure software delivery practices.

Security & Responsible AI

• Strong understanding of secure and responsible AI principles.
• Experience handling sensitive and classified data.
• Knowledge of security controls and governance requirements in high-security environments.

Security Clearance Requirements

Candidates must be eligible for security clearance at a minimum level of:

• Norwegian SECRET
  and/or
• NATO SECRET

Language Requirements

• Fluent Norwegian language proficiency (minimum C1 level)

Preferred Profile

We are looking for an experienced and versatile AI Engineer who:

• Takes ownership and accountability for delivering high-quality solutions.
• Works in a structured and disciplined manner.
• Understands the importance of security, resilience, reliability, and quality in mission-critical environments.
• Can translate advanced AI concepts into practical, scalable business and operational solutions.
• Collaborates effectively across multidisciplinary teams.
• Communicates clearly with both technical and non-technical stakeholders.
• Contributes positively to team success and delivery excellence.
• Demonstrates a strong commitment to continuous learning and professional growth.

Why Join IBM Defense & Intelligence?

Become part of a highly specialized technology environment where your work directly impacts:

• National security
• Defense readiness
• Operational decision support
• NATO and allied defense capabilities

You will work alongside experts in AI, cloud, security, and defense technologies to solve some of the most complex and meaningful challenges facing modern defense organizations.

About IBM Consulting

IBM Consulting is IBM's global consulting and professional services business, helping organizations transform through business strategy, technology innovation, and operational excellence.

With deep expertise across industries and emerging technologies, IBM Consulting delivers transformative solutions through Hybrid Cloud, Artificial Intelligence, and enterprise modernization initiatives. Our teams collaborate with some of the world's most innovative organizations to accelerate business outcomes and drive sustainable growth.

Life at IBM

At IBM, innovation, trust, and continuous learning are at the core of everything we do. Employees are encouraged to:

• Explore new ideas and technologies.
• Develop professionally through ongoing learning opportunities.
• Collaborate across diverse teams and disciplines.
• Contribute to meaningful projects with real-world impact.
• Grow their careers in an inclusive and supportive environment.

About IBM

Since 1911, IBM has been a global leader in technology innovation, helping organizations harness the power of artificial intelligence, hybrid cloud, quantum computing, blockchain, and advanced analytics.

IBM remains committed to building responsible technology that improves business, society, and the human condition.

Equal Opportunity Employer

IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or any other legally protected status.

IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

Flexible Working

IBM encourages employees to bring their whole selves to work and supports flexible working arrangements where business requirements permit. Candidates interested in flexible working options are encouraged to discuss possibilities with the recruitment team during the hiring process.

Location: Dallas, Texas | Chicago, Illinois | New York, USA
Job Type: Full-Time | Professional
Education Required: Bachelor's Degree
Preferred Education: Master's Degree
Company: IBM Consulting

Job Summary

IBM Consulting is seeking a highly experienced Senior AI Architect – Azure & Cloud AI to join its rapidly growing AI practice. This is a senior-level, client-facing position focused on delivering enterprise-scale AI transformation initiatives across cloud and hybrid environments.

As a trusted technical leader, you will define AI strategy, establish enterprise architecture standards, and guide the implementation of scalable, secure, and governed AI solutions. You will work closely with executive stakeholders, business leaders, data teams, and engineering organizations to ensure AI investments align with measurable business outcomes.

This role is ideal for professionals with extensive experience in Azure AI, Agentic AI, Large Language Models (LLMs), cloud architecture, AI governance, and enterprise solution delivery.

Key Responsibilities

AI Strategy & Technical Leadership

• Serve as the primary technical authority across complex AI transformation programs.
• Define and govern enterprise AI architecture standards and best practices.
• Establish architectural vision and technical direction across multiple AI workstreams.
• Develop reusable reference architectures, frameworks, and accelerators.
• Mentor architects, engineers, and AI practitioners on Azure AI technologies and emerging innovations.
• Drive AI adoption strategies that align with enterprise business goals.

Client Engagement & Enterprise Architecture

• Lead architecture workshops, design sessions, and stakeholder engagements.
• Translate business requirements into scalable and secure AI-powered solutions.
• Present technical recommendations to both executive and technical audiences.
• Align AI use cases with measurable business value and ROI.
• Ensure governance, compliance, security, and operational standards are incorporated from project inception.

Azure AI Solution Architecture

• Architect enterprise AI platforms using:
  • Azure OpenAI
  • Azure Machine Learning (Azure ML)
  • Azure Data Services
  • Enterprise Data Platforms
• Define architecture standards for:
  • Model deployment
  • Prompt engineering
  • Data integration
  • AI observability
  • Monitoring and governance
• Design scalable operating models for AI industrialization, including deployment, support, governance, and lifecycle management.

Agentic AI & Enterprise AI Integration

• Design and implement Agentic AI architectures.
• Leverage Model Context Protocols (MCPs) for secure integration between:
  • AI agents
  • Enterprise applications
  • Data platforms
  • Business systems
• Develop orchestration frameworks and guardrails for agentic workflows.
• Implement human-in-the-loop controls, auditability, and AI governance mechanisms.
• Enable interoperability and extensibility across enterprise AI ecosystems.

Enterprise Delivery & Governance

• Ensure AI solutions meet enterprise security, compliance, and reliability requirements.
• Collaborate with business, engineering, security, and data teams.
• Support AI platform strategy, architecture reviews, vendor selection, and governance initiatives.
• Drive adoption of enterprise AI best practices and responsible AI standards.

Required Qualifications

Education

• Bachelor's Degree (Required)
• Master's Degree (Preferred)

Experience

• 8+ years of experience designing and delivering enterprise-scale AI and Agentic AI solutions.
• Proven experience implementing AI solutions across cloud and hybrid environments.
• Extensive expertise in Azure and AWS cloud platforms.

Technical Skills

AI & Cloud Architecture

• Azure OpenAI
• Azure Machine Learning (Azure ML)
• Azure AI Services
• AWS AI & Cloud Services
• Enterprise AI Platform Architecture

Large Language Models & Agentic AI

• LLM-powered application development
• Agentic AI architecture design
• Multi-agent orchestration
• Tool calling frameworks
• Memory management
• Model Context Protocols (MCP)
• Human-in-the-loop architectures

AI Frameworks & Development

• LangChain
• LangGraph
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• AI Workflow Automation

AI Operations & Governance

• AI Industrialization
• Model Lifecycle Management (ML Ops)
• CI/CD for AI Systems
• AI Monitoring & Observability
• Evaluation Frameworks
• Prompt & Version Management
• Guardrail Frameworks
• Responsible AI Practices

Enterprise Integration

• APIs and Microservices
• Enterprise Applications
• Vector Databases
• Workflow Automation Platforms
• Data Integration Solutions

Preferred Skills

• Experience with Agentic AI frameworks such as:
  • LangChain
  • AutoGen
  • Semantic Kernel
• Experience with Microsoft data platforms:
  • Azure Synapse Analytics
  • Azure Data Factory
  • Microsoft Fabric
• Knowledge of:
  • Responsible AI
  • AI Governance
  • Enterprise Security Frameworks
  • Regulatory Compliance Requirements

Preferred Certifications

• Azure Solutions Architect Expert
• Azure AI Engineer Associate
• Other Microsoft Azure Certifications

Why Join IBM Consulting?

IBM Consulting helps organizations transform their businesses through AI, cloud computing, and emerging technologies. You will work alongside industry-leading experts and global clients to solve complex business challenges using innovative AI solutions.

Benefits & Perks

Eligible employees may receive access to:

Health & Wellness Benefits

• Medical Insurance
• Prescription Drug Coverage
• Dental Insurance
• Vision Coverage
• Mental Health & Well-being Programs

Financial Benefits

• 401(k) Program
• Cash Balance Pension Plan
• IBM Employee Stock Purchase Plan (ESPP)
• Life Insurance
• Financial Counseling
• Short-Term Disability Coverage
• Long-Term Disability Coverage
• Performance-Based Incentive Programs

Paid Time Off

• 12 Paid Holidays
• Minimum 56 Hours Sick Leave
• 120 Hours Vacation
• 12 Weeks Parental Bonding Leave
• Paid Family Care Leave Programs

Learning & Development

• AI-powered personalized learning platform
• Professional certification support
• Continuous technical training
• Career development opportunities

Diversity & Inclusion

• Employee Resource Groups
• Volunteer & Community Programs
• Retail, Service & Experience Discounts
• Inclusive and collaborative workplace culture

Important Employment Information

Visa Sponsorship

IBM will not provide visa sponsorship for this position now or in the future. Applicants must be authorized to work in the United States without requiring current or future visa sponsorship.

Compensation

Compensation will vary based on:

• Skills and qualifications
• Professional experience
• Geographic location
• Employment classification

Benefits and compensation may be adjusted for part-time employees and individuals joining during the calendar year.

Equal Opportunity Employer

IBM is committed to creating a diverse and inclusive workplace. Qualified applicants will receive consideration for employment regardless of race, color, religion, sex, gender identity, sexual orientation, national origin, disability, age, veteran status, genetic information, neurodiversity, citizenship status, or any other protected characteristic under applicable law.

Location: Brasov, Cluj-Napoca, Timisoara, Bucharest, Romania
Job Type: Professional / Full-Time
Education Required: Bachelor's Degree
Company: IBM

Job Overview

IBM Consulting is seeking an experienced AI Architect (Forward Deployed Engineer) to establish enterprise architecture across data, applications, and technology while driving AI-augmented software delivery models. The role focuses on translating enterprise architecture into production-ready solutions that integrate Generative AI and Agentic AI capabilities while maintaining security, compliance, performance, and ethical AI standards.

As an AI Architect, you will collaborate with business stakeholders, product managers, designers, developers, and AI-powered digital workers to build innovative solutions that accelerate business value. This position combines expertise in enterprise architecture, AI engineering, application development, integration, and platform architecture.

Key Responsibilities

Enterprise Architecture & Solution Design

• Define overall enterprise architecture, AI agents, and delivery models.
• Collaborate with client business teams and translate business requirements into scalable component models.
• Design data architecture, application architecture, and technology architecture.
• Make architectural decisions regarding technology selection, data sources, AI adoption, and enterprise integration.
• Define ethical AI adoption frameworks within client organizations.

AI & Agentic Engineering

• Design and build AI agents and digital assistants to accelerate product development.
• Establish AI-augmented development frameworks across the Software Development Life Cycle (SDLC).
• Develop standards for context engineering and AI-assisted coding practices.
• Implement enterprise-wide AI solutions and coding engines.
• Build agentic AI applications and LLM-powered workflows.
• Work with MCP servers, tool connectors, and LLM orchestration frameworks.

SDLC Automation & Delivery Excellence

• Define AI-driven workflows that augment software development lifecycles.
• Integrate AI agents and assistants across SDLC activities.
• Collaborate with full-stack engineering teams on data models and high-level solution design.
• Establish AI-powered static code analysis and unit test coverage strategies.
• Design AI-based testing frameworks and deployment models.
• Define and implement DevOps and CI/CD pipelines.
• Create Infrastructure as Code (IaC)-based deployment approaches.

Enterprise Integration & Governance

• Partner with enterprise integration architects on system and agent integration strategies.
• Document architecture decisions and asset utilization through Architecture Decision Documents (ADDs).
• Define standards for AI-assisted development, testing, documentation, and delivery acceleration.
• Support adoption of AI-powered assistants and GenAI tools throughout the SDLC lifecycle.

Required Qualifications

Education

• Bachelor's Degree

Required Technical & Professional Expertise

• Strong experience defining enterprise architecture for business digitalization initiatives.
• Deep understanding of business value streams, data models, application architectures, and technology platforms.
• Expertise in AI-augmented software development and enterprise AI adoption.
• Experience implementing AI coding engines throughout software development lifecycles.
• Strong knowledge of context engineering principles.
• Ability to make strategic architecture decisions across business applications, data sources, and AI implementations.
• Experience with MCP servers, tool connectors, and LLM orchestration frameworks.
• Hands-on experience building agentic AI solutions and intelligent workflow automation.
• Expertise in CI/CD pipeline design and implementation.
• Experience developing Infrastructure as Code (IaC) deployment models.
• Strong enterprise integration and architecture governance experience.

Required Certifications

Candidates must possess one of the following certifications:

• TOGAF Level 2 Certification
  OR
• Open Group Master Certified Architect

Required AI Tools & Platforms Experience

Coding & Development Agents

• GitHub Copilot
• Roo / Cline
• Cursor
• Visual Studio Code with AI-assisted development workflows
• ChatGPT for code generation, debugging, and documentation

AI-Augmented Collaboration & Product Delivery

• Miro with AI-assisted ideation and workflow mapping
• Jira for Agile delivery and AI-supported backlog management
• Confluence for AI-enhanced documentation and knowledge sharing

Enterprise Architecture & SDLC Enablement

• LeanIX
• AI-powered SDLC assistants
• Workflow automation platforms
• AI-assisted requirements analysis, testing support, documentation generation, and delivery acceleration tools

Why Join IBM Consulting?

IBM Consulting delivers deep industry expertise and advanced technology solutions to public and private sector clients worldwide. Working within IBM Client Innovation Centers, you will help organizations accelerate digital transformation through AI, cloud, and emerging technologies.

What IBM Offers

• Opportunities to work on cutting-edge AI and enterprise transformation projects.
• Continuous learning and professional development.
• Collaborative and innovation-driven culture.
• Exposure to global clients and complex enterprise environments.
• Inclusive workplace committed to diversity, equity, and equal opportunity.

About IBM

Founded in 1911, IBM is one of the world's leading technology and consulting organizations. IBM continues to lead innovation across artificial intelligence, hybrid cloud, quantum computing, blockchain, and enterprise technology solutions. IBM empowers businesses worldwide through responsible technology innovation and digital transformation.

Equal Opportunity Employer

IBM is proud to be an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, genetics, pregnancy, disability, neurodiversity, age, citizenship, immigration status, or any other protected characteristic under applicable law.

Flexible Working

IBM encourages flexible working arrangements where business needs permit. Candidates interested in flexible work options are encouraged to discuss available arrangements with the recruitment team during the hiring process.

Job Overview

Amazon Web Services (AWS) is seeking an experienced and innovative Principal Applied Scientist to join the Quick Science Team, the organization behind AWS's enterprise-grade Generative AI assistant known as Quick.

Quick empowers enterprise users by helping them answer questions, summarize documents, generate content, automate workflows, perform actions, and access information across multiple enterprise systems. This role offers an exceptional opportunity to lead cutting-edge research and development initiatives in Generative AI, Agentic AI, Large Language Models (LLMs), and Multi-Modal AI Systems.

As a Principal Applied Scientist, you will play a critical leadership role in advancing intelligent AI agents capable of complex reasoning, autonomous decision-making, and workflow automation that significantly improve enterprise productivity at scale.

Job ID

10441249

About the Role

The Quick Science Team is building the future of enterprise AI assistants by combining state-of-the-art Generative AI technologies with intelligent agent architectures.

In this role, you will lead scientific innovation and contribute directly to the development of advanced AI systems capable of:

• Complex reasoning and decision-making
• Enterprise workflow automation
• Multi-step task execution
• Content generation and summarization
• Knowledge retrieval and information synthesis
• Intelligent agent orchestration
• Multi-modal understanding across text, documents, and enterprise data

You will collaborate closely with software engineers, machine learning experts, product leaders, and executive stakeholders to transform scientific research into scalable customer-facing solutions.

Key Responsibilities

Lead Advanced AI Research

• Drive research initiatives focused on Generative AI and Agentic AI technologies.
• Develop innovative approaches for intelligent enterprise assistants.
• Explore new methodologies for autonomous reasoning and workflow automation.
• Advance the state of the art in Large Language Models and foundation model applications.

Build and Optimize Foundation Models

• Design, train, and fine-tune state-of-the-art Large Language Models (LLMs).
• Develop and improve multi-modal foundation models.
• Enhance model performance, scalability, and reliability.
• Evaluate and implement cutting-edge AI architectures.

Develop Intelligent Agent Systems

• Architect autonomous AI agents capable of complex task execution.
• Design systems that support multi-step planning and decision-making.
• Improve agent orchestration and workflow automation capabilities.
• Build scalable frameworks for enterprise AI deployments.

Collaborate Across Teams

• Partner with engineering teams to bring AI research into production.
• Work closely with product managers and business stakeholders.
• Influence strategic technology decisions across the organization.
• Drive cross-functional collaboration on high-impact AI initiatives.

Scientific Leadership

• Mentor scientists and researchers across multiple teams.
• Promote best practices in machine learning and AI development.
• Guide technical strategy and long-term innovation roadmaps.
• Contribute to the scientific growth of AWS AI organizations.

Required Qualifications

Educational Requirements

Candidates must possess one of the following:

• PhD in:
  • Machine Learning
  • Computer Science
  • Electrical Engineering
  • Artificial Intelligence
  • Related Technical Discipline

OR

• Master's Degree with 5+ years of relevant industry or research experience.

Technical Experience

Applicants should demonstrate experience in:

• Developing machine learning models for real-world applications.
• Building Generative AI systems and AI-powered solutions.
• Training, fine-tuning, or deploying foundation models.
• Research and development within Artificial Intelligence and Machine Learning domains.
• Programming using Python or similar development languages.

Research Achievements

Candidates should have a proven track record of:

• Peer-reviewed scientific publications.
• Granted patents.
• Significant contributions to Artificial Intelligence or Machine Learning research.

AI Domain Expertise

Experience in at least one of the following areas:

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Computer Vision
• Agentic AI Systems

Preferred Qualifications

Generative AI and Enterprise Applications

Experience applying AI technologies to:

• Enterprise productivity solutions
• Document understanding systems
• Code generation platforms
• Task planning and automation systems
• Multi-modal AI applications

Agentic AI Expertise

Strong knowledge of:

• Agent-based architectures
• Autonomous systems
• AI planning frameworks
• Multi-agent coordination
• Workflow orchestration technologies

Machine Learning Infrastructure

Hands-on experience with:

• Distributed model training
• Scalable AI infrastructure
• Large-scale machine learning systems
• Foundation model optimization
• High-performance AI platforms

AI Safety and Reliability

Understanding of:

• AI safety frameworks
• Hallucination mitigation techniques
• Retrieval-Augmented Generation (RAG)
• Responsible AI principles
• Model evaluation and governance

Leadership Skills

Proven ability to:

• Mentor junior scientists and technical teams.
• Influence organizational strategy.
• Communicate technical concepts to non-technical audiences.
• Collaborate effectively with senior leadership and executive stakeholders.

Product Innovation

Track record of:

• Delivering scientific innovations into production.
• Launching customer-facing AI products at scale.
• Transforming research into measurable business impact.

Salary and Compensation

Amazon offers a highly competitive compensation package that includes base salary, sign-on bonuses, Restricted Stock Units (RSUs), and comprehensive employee benefits.

Salary Range by Location

Santa Clara, California

• $228,700 – $309,400 USD annually

New York, New York

• $218,800 – $295,900 USD annually

Seattle, Washington

• $198,900 – $269,000 USD annually

Final compensation will depend on experience, qualifications, skills, and geographic location.

Employee Benefits

Financial Benefits

• Competitive base salary
• Sign-on bonus opportunities
• Restricted Stock Units (RSUs)
• 401(k) retirement savings plan with company matching

Health and Wellness

• Medical Insurance
• Dental Insurance
• Vision Coverage
• Prescription Drug Coverage
• Basic Life Insurance
• AD&D Insurance
• Supplemental Life Insurance Options
• Employee Assistance Program (EAP)
• Mental Health Support Services
• Medical Advice Line

Family and Lifestyle Benefits

• Paid Time Off (PTO)
• Parental Leave
• Flexible Spending Accounts (FSA)
• Adoption Assistance Programs
• Surrogacy Reimbursement Coverage

Why Join AWS Agentic AI?

This is a rare opportunity to shape the future of enterprise Artificial Intelligence while working on some of the most advanced AI technologies in the world.

By joining AWS Agentic AI, you will:

• Work on next-generation Generative AI and Agentic AI systems.
• Influence products used by enterprises worldwide.
• Collaborate with leading AI scientists and engineers.
• Drive innovation in intelligent automation and autonomous reasoning.
• Access world-class infrastructure and computational resources.
• Transform research breakthroughs into impactful customer solutions.

Diversity, Inclusion, and Equal Opportunity

Amazon is committed to building an inclusive workplace where innovation thrives through diverse experiences and perspectives.

The company provides equal employment opportunities regardless of race, gender, disability, veteran status, or any other protected characteristic. Qualified applicants, including those with arrest and conviction records where applicable by law, will receive fair consideration for employment.

Amazon also provides reasonable accommodations throughout the hiring and onboarding process for individuals with disabilities.

Apply for Principal Applied Scientist – AWS Agentic AI

If you are passionate about Generative AI, Agentic AI, Large Language Models, Machine Learning Research, Multi-Modal AI, Intelligent Automation, and Enterprise AI Innovation, this role provides an opportunity to lead transformative AI initiatives at one of the world's most influential technology companies.

Apply today and help build the future of intelligent enterprise AI with AWS.