Job ID: P-78

Help Build the Infrastructure Behind the Future of AI

At Databricks, we are committed to helping data and AI teams solve some of the world’s most challenging problems—from advancing healthcare innovation to enabling next-generation transportation technologies. Our mission is powered by building and operating the industry’s leading Data Intelligence Platform, enabling organizations to transform data into actionable insights and AI-driven outcomes.

We are seeking a Senior Software Engineer (Backend) – AI/ML Environments to join our growing ML/AI Environments team. This is a unique opportunity to build foundational AI infrastructure that empowers researchers, data scientists, and machine learning engineers to create, train, and deploy AI models efficiently and at scale.

As part of one of Databricks’ fastest-growing businesses, Mosaic AI, you’ll help build the systems powering the next generation of enterprise AI.

About the ML/AI Environments Team

The ML/AI Environments team develops the infrastructure that enables AI researchers and engineers to create customized training and serving environments for machine learning workloads.

The team’s mission is to make AI development:

• Easy to configure
• Reliable to operate
• Reproducible across environments
• Scalable for enterprise workloads

Working at the intersection of AI infrastructure, developer productivity, and cloud-native systems, you’ll collaborate closely with research, product, and engineering teams to deliver capabilities that directly impact thousands of Databricks customers.

Your Impact

As a Senior Backend Engineer, you’ll play a critical role in shaping how machine learning practitioners build and interact with AI applications on the Databricks platform.

Your work will influence everything from environment creation and dependency management to performance optimization and operational visibility.

Key Responsibilities

Build AI Environment Infrastructure

• Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably, and reproducibly.
• Develop systems that simplify environment setup while ensuring consistency across machine learning workflows.
• Support scalable AI development experiences across a wide range of use cases.

Partner Across AI Infrastructure Teams

• Collaborate with other AI infrastructure teams to deliver features that enhance customer productivity.
• Contribute to platform-wide improvements that increase efficiency and reliability.
• Work on initiatives that help customers maximize the value of the Databricks platform.

Examples include:

• Improving virtual environment setup performance for short-duration training and data processing jobs.
• Enhancing observability capabilities to simplify debugging and failure analysis.
• Optimizing infrastructure workflows for AI development and deployment.

Drive Customer-Focused Innovation

• Engage directly with turnkey customers and product managers.
• Help identify product improvements and new feature opportunities.
• Translate customer feedback into scalable engineering solutions.

Shape the Future of AI Development

• Influence how developers, machine learning engineers, and data scientists build and interact with AI on Databricks.
• Contribute to platform experiences that accelerate AI adoption across organizations.
• Help define the next generation of AI infrastructure tooling.

What We’re Looking For

Backend & Infrastructure Engineering Experience

• 5+ years of experience in backend engineering, infrastructure engineering, or related systems-focused software development roles.
• Proven experience building production-grade systems and platform infrastructure.

Programming Expertise

Strong programming skills in one or more of the following languages:

• Python
• Scala
• Java

Distributed Systems Knowledge

Experience working with:

• Distributed systems
• Scalable APIs
• Cloud-native infrastructure
• High-performance backend services

Platform Engineering Fundamentals

Familiarity with:

• Service-oriented architecture (SOA)
• Deployment pipelines
• System observability
• Infrastructure reliability practices

Product Ownership Mindset

• Strong product and ownership mentality.
• Focus on building the right solution rather than simply delivering technical implementations.
• Ability to balance customer needs with engineering excellence.

Dependency Management & Environment Technologies

Strong understanding of dependency management technologies, including:

• Virtual environments
• Containerization technologies

Experience supporting reproducible development and deployment workflows is highly valued.

Why This Role Matters

The future of AI depends on infrastructure that is reliable, scalable, and easy to use.

In this role, you’ll help build the foundation that enables:

• Machine Learning Engineers
• Data Scientists
• AI Researchers
• Enterprise Development Teams

to develop, train, and serve AI applications more effectively.

Your contributions will directly impact the AI development lifecycle across thousands of organizations worldwide.

Compensation & Pay Transparency

Databricks is committed to fair and equitable compensation practices.

Local Pay Range

$166,000 — $220,000 USD

Compensation is determined based on several factors, including:

• Relevant technical expertise
• Professional experience
• Certifications and specialized training
• Geographic location
• Job-related skills

The total compensation package may also include:

• Annual performance bonuses
• Equity awards
• Comprehensive employee benefits

Databricks anticipates utilizing the full salary range based on candidate qualifications and experience.

About Databricks

Databricks is the Data and AI company trusted by more than 10,000 organizations worldwide.

Leading enterprises—including Comcast, Condé Nast, Grammarly, and more than 50% of Fortune 500 companies—rely on the Databricks Data Intelligence Platform to unify data, analytics, and artificial intelligence.

Databricks was founded by the original creators of:

• Apache Spark™
• Delta Lake
• MLflow
• Lakehouse Architecture

Headquartered in San Francisco, Databricks continues to lead innovation across data engineering, machine learning, analytics, and AI infrastructure.

Benefits

Databricks offers a comprehensive benefits package designed to support employees throughout every stage of their career and personal journey. Benefits and perks may vary by region and location.

Diversity, Equity & Inclusion

Databricks is committed to fostering a diverse and inclusive workplace where every individual has the opportunity to succeed.

Employment decisions are made without regard to age, race, ethnicity, religion, disability, family status, gender identity, sexual orientation, veteran status, political affiliation, socio-economic background, or any other protected characteristic.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer’s discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Apply for Senior Software Engineer (Backend) – AI/ML Environments Jobs at Databricks

If you’re passionate about backend engineering, distributed systems, cloud infrastructure, AI platform development, and building tools that empower the next generation of machine learning innovation, this is an opportunity to make a meaningful impact at one of the world’s leading Data and AI companies.