Our team designs trains and deploys large-scale neural networks optimized for inference on compute-constrained edge devices CPU GPU custom AI ASIC.
This role sits at the intersection of ML modeling and hardware-aware systems engineering - you will architect and train state-of-the-art models while co-designing them with the underlying silicon and compiler stack to maximize performance.
You will drive the full lifecycle from model research and training at scale to quantized latency-optimized deployment across Teslas heterogeneous compute platforms.
Design train and iterate on neural network architectures for autonomous driving and robotics with a focus on efficiency-aware model design architecture search distillation pruning quantization-aware training
Co-design model architectures with compiler and ASIC teams to exploit hardware-specific capabilities custom ops dataflow patterns memory hierarchy
Develop and optimize the model lowering and deployment pipeline from PyTorch to edge inference on Teslas in-house AI ASIC
Profile and optimize end-to-end inference latency and throughput across heterogeneous compute targets
Implement custom CUDA GPU kernels for training post-processing or operations not natively supported by frameworks
Collaborate with AI teams on translating modeling breakthroughs into production-ready hardware-efficient implementations
Strong foundation in deep learning hands-on experience designing training and debugging neural network architectures transformers convnets diffusion models etc.
Proficiency with PyTorch or equivalent framework including distributed training custom autograd ops and mixed-precision workflows
Proficiency with Python and CC modern C1720 preferred
Solid understanding of computer architecture and systems concepts memory hierarchy instruction pipelines accelerator design
Experience with model optimization techniques quantization pruning knowledge distillation or neural architecture search
Experience with CUDA or GPU kernel development
Familiarity with ML compiler stacks or model lowering toolchains e.g. TVM XLA MLIR TensorRT is a plus
Benefits
Along with competitive pay as a full-time Tesla employee you are eligible for the following benefits at day 1 of hire
Medical plans > plan options with 0 payroll deduction Family-building fertility adoption and surrogacy benefits Dental including orthodontic coverage and vision plans both have options with a 0 paycheck contribution Company Paid Health Savings Accounts HSA Contribution when enrolled in the High-Deductible medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts FSA 401k with employer match Employee Stock Purchase Plans and other financial benefits Company paid Basic Life AD&D Short-term and long-term disability insurance 90 day waiting period Employee Assistance Program Sick and Vacation time Flex time for salary positions Accrued hours for Hourly positions and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include critical illness hospital indemnity accident insurance theft & legal services and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program
Expected Compensation
132000 - 390000annual salary cash and stock awards benefits
Pay offered may vary depending on multiple individualized factors including market location job-related knowledge skills and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.