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Sr. Software Engineer, Model Scaling, AI Infrastructure
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Tesla Motors, Inc.
Palo Alto, CA (In Person)
Full-Time
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Job Description
Sr. Software Engineer, Model Scaling, AI Infrastructure Tesla Motors, Inc. 176,000 - 558,000 USD paid holidays, flex time, 401(k) United States, California, Palo Alto Jun 17, 2026
What to Expect We are looking for strong software engineers to help
scale 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 ML
practitioners and infrastructure engineers to improve training efficiency,
accelerate experimentation, and enable larger and more capable models. The ideal candidate is excited about both systems and
machine learning. You should be comfortable debugging distributed training
issues, analyzing model behavior, and using data to demonstrate how
infrastructure improvements translate into better model quality. You will help build and optimize large-scale training
systems running on thousands of GPUs while developing the tools, metrics, and
workflows needed to make model scaling faster and more predictable. What You'll Do
Optimize large-scale distributed training across
thousands 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 across
PyTorch, CUDA, communication libraries, and training frameworks
Partner with researchers to evaluate how infrastructure
changes impact model quality, convergence, and downstream metrics
Analyze training runs and build dashboards that connect
system performance to model outcomes
Drive improvements in model scaling efficiency, including
larger models, longer context lengths, and higher-quality datasets
Debug complex issues across software, hardware,
networking, and machine learning systems
Build infrastructure that accelerates experimentation and
shortens iteration cycles for researchers What You'll Bring
Strong software engineering fundamentals in Python and
C++
Experience with distributed systems, high-performance
computing, or large-scale infrastructure
Understanding of machine learning fundamentals, including
optimization, training dynamics, and evaluation
Familiarity with PyTorch and modern deep learning
frameworks
Ability to analyze performance bottlenecks using
profiling and observability tools
Strong debugging and problem-solving skills
Excellent communication and collaboration skills Compensation and Benefits
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
Expected Compensation
$176,000 - $558,000/annual 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.