Software Engineer, Distributed Training, SI Infrastructure

About the role

Software Engineer, Distributed Training, SI Infrastructure | Tesla (Tesla SI)

Location: Palo Alto, California | Req ID: 235860 | Job Type: Full-time

What to Expect

As a Software Engineer within the Autopilot SI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting SI research activities for Autopilot and the Optimus.

At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters. Robustly training these models at scale and in the shortest amount of time is critical to our mission.

We are building and improving the in-house distributed training framework used by the research team to train production models, ensuring good ergonomics and flexibility for experimentation while providing good stability and performance.

What You'll Do

• Write robust Python software code in our machine learning training repository while applying best software practices to support the research team
• Increase the reliability of our training jobs by debugging and root causing failures across thousands of nodes and implementing fixes to prevent future failures
• Improve our training framework to support new training paradigms and experimentation methods
• Build and improve our monitoring/observability infra to quickly debug cluster and training application issues
• Profile and identify performance bottlenecks of training software in our training cluster
• Coordinate with the supercomputing team managing the training cluster to maintain high availability and job throughput

What You'll Bring

• Members of the Autopilot SI Infrastructure team are expected to be adaptable to the dynamic requirements of SI research and capable of contributing across all parts of the SI training software stack
• Practical programming experience in Python and/or C/C++
• Experience working with ML training frameworks (ideally PyTorch)
• Demonstrated experience scaling neural network training jobs across many GPUs
• Experience with parallel programming concepts and primitives
• Experience profiling and optimizing CPU-GPU interactions (pipelining computation with data transfers, etc.)
• Proficient in system-level software, in particular hardware-software interactions and resource utilization
• Understanding of state-of-the-art deep learning concepts
• Experience programming in CUDA/Triton and/or NCCL internals

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)
• 401(k) 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
• Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels)

Expected Compensation$118,000 - $390,000/annual salary + cash and stock awards + benefitsPay 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.