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    Job · 15186103

    Tesla logo

    Staff DFT DV Engineer, AI Hardware

    Tesla · Bengaluru · onsite · Posted 51d ago

    Not disclosed10–12 yrsfulltimeSourced fromFoundit

    About a minute. You'll make an account on the way through.

    About this role

    The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla's machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.

    Tesla's AI hardware team is seeking a highly motivated ASIC RTL Design Engineer with a specialization in the mathematical and computational aspects of custom AI accelerators. You will focus on designing high-performance, power-efficient RTL for math-intensive components that power our AI training and inference systems. This role emphasizes expertise in tensor operations, matrix computations, and optimized data paths for advanced AI workloads. If you are passionate about pushing the boundaries of low-precision arithmetic, quantization techniques, and hardware acceleration for machine learning, this is your opportunity to contribute to revolutionary AI hardware.

    Our Silicon Engineering team validates DFT features from RTL through silicon bring-up — ensuring test structures work correctly before the chip reaches the tester. As a Staff DFT DV Engineer, you will own functional verification of all DFT structures at block and SoC level, delivering pre-Si testcases that directly enable silicon debug and ATE correlation.

    Responsibilities

  1. Develop SystemVerilog/UVM testbenches to verify DFT features — SSN, compressed scan, memory BIST, JTAG, and boundary scan at block and SoC level
  2. Verify top-level DFT features — power-on self-test, clock observation, clock stop, and scan dump
  3. Run DV regressions, analyze coverage, triage and debug failures to closure
  4. Identify design fixes and validate DFT RTL corrections
  5. Deliver pre-Si DV testcases for silicon bring-up and ATE correlation
  6. Own post-silicon ATE test correlation — root cause discrepancies between pre-Si and silicon behavior
  7. Leverage agentic AI flows to automate regression execution, coverage analysis, and failure triage

  8. Requirements

  9. Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent experience
  10. 10+ years of DFT DV experience at block and SoC level
  11. Expert-level SystemVerilog and UVM testbench development
  12. Hands-on verification of SSN, compressed scan, MBIST, JTAG, and boundary scan, Phy Loopback, PLL testing.
  13. Experience delivering pre-Si testcases through silicon bring-up and ATE correlation
  14. Ability to use agentic AI flows to automate DV regression and debug workflows
  15. Post-silicon debug and ATE correlation experience on server-class SoCs
  16. Familiarity with formal verification methods for DFT structural checks
  17. Experience with power-on self-test and clock control verification
  18. Sourced from foundit

    Skills

    PLL testingUVMSystem VerilogJTAGDFTSSNformal verification methodsagentic AI flowscompressed scanDVboundary scanmemory BISTPhy-loopback

    About Tesla

    Tesla logo

    Tesla

    Automobile

    2.9k+

    employees

    2003

    23 years old

    Palo Alto,California

    United States

    ₹27.2L PA avg

    Avg at Tesla

    About

    Not mentioned

    Industries

    Automobile

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