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.