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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.
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Manufacturer of electric vehicles, battery storage, and solar technology.
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Mid · 3+ years experience
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