Tesla
Website:
tesla.com
Job details:
Position Description
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. This role is located in Bengaluru, India. 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
Develop SystemVerilog/UVM testbenches to verify DFT features — SSN, compressed scan, memory BIST, JTAG, and boundary scan at block and SoC level Verify top-level DFT features — power-on self-test, clock observation, clock stop, and scan dump Run DV regressions, analyze coverage, triage and debug failures to closure Identify design fixes and validate DFT RTL corrections Deliver pre-Si DV testcases for silicon bring-up and ATE correlation Own post-silicon ATE test correlation — root cause discrepancies between pre-Si and silicon behavior Leverage agentic AI flows to automate regression execution, coverage analysis, and failure triage
Requirements
Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent experience 3+ years of DFT DV experience at block and SoC level Expert-level SystemVerilog and UVM testbench development Hands-on verification of SSN, compressed scan, MBIST, JTAG, and boundary scan Experience delivering pre-Si 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
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