Software Engineer, Frontier SI Infrastructure

What to Expect

We are looking for strong software engineers to helpscale the next generation of large AI models for Autopilot, Optimus &Digital Optimus. This role sits at the intersection of distributed systems,machine learning, and performance engineering. You will work closely with MLpractitioners and infrastructure engineers to improve training efficiency,accelerate experimentation, and enable larger and more capable models.

The ideal candidate is excited about both systems andmachine learning. You should be comfortable debugging distributed trainingissues, analyzing model behavior, and using data to demonstrate howinfrastructure improvements translate into better model quality.

You will help build and optimize large-scale trainingsystems running on thousands of GPUs while developing the tools, metrics, andworkflows needed to make model scaling faster and more predictable.

What You’ll Do

• Optimize large-scale distributed training acrossthousands of GPUs
• Improve training throughput, utilization, reliability,and scalability
• Develop tooling to identify bottlenecks in compute,networking, memory, and data pipelines
• Design and implement performance optimizations acrossPyTorch, CUDA, communication libraries, and training frameworks
• Partner with researchers to evaluate how infrastructurechanges impact model quality, convergence, and downstream metrics
• Analyze training runs and build dashboards that connectsystem performance to model outcomes
• Drive improvements in model scaling efficiency, includinglarger models, longer context lengths, and higher-quality datasets
• Debug complex issues across software, hardware,networking, and machine learning systems
• Build infrastructure that accelerates experimentation andshortens iteration cycles for researchers

What You’ll Bring

• Strong software engineering fundamentals in Python andC++
• Experience with distributed systems, high-performancecomputing, or large-scale infrastructure
• Understanding of machine learning fundamentals, includingoptimization, training dynamics, and evaluation
• Familiarity with PyTorch and modern deep learningframeworks
• Ability to analyze performance bottlenecks usingprofiling and observability tools
• Strong debugging and problem-solving skills
• Excellent communication and collaboration skills

Compensation and 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

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.