What to Expect
Scaling transformers, as well as more recent advances in Reinforcement Learning with Verifiable Rewards (RLVR), has created models with Ph-D level intelligence in a wide variety of subject areas – from Math to Social Sciences. Yet these models continue to struggle in real-world physical reasoning, often struggling to tell left from right.
At Tesla AI, we want to develop Olympiad-level physical intelligence that will enable highly capable robots, both wheeled and legged. These models should be able to anticipate and reason about future movements of any object or scene at the level of a race car driver or professional athlete. To accomplish this, you will have access to petabytes of multimodal (video, audio, action etc.) real-world data from our global fleet of cars and robots, as well as Tesla’s state-of-the-art compute resources.
In this role, you will have the opportunity to work on the datasets, infra, model architecture, eval and scaling laws necessary to pretrain a large multimodal model with an emphasis on real-world physical intelligence.

What You’ll Do

• Design, train, and evaluate models optimized for edge accelerators
• Focus on improving model quality and training stability with model architecture design
• Conduct scaling laws for model architecture and parallelism-aware compute efficiency
• Work closely with AI engineers, compiler engineers, and hardware engineers to push the frontier of intelligence per watt
• Design novel model architectures and algorithms for scaling and hardware utilization
• Innovate in domains such as sparsity, distillation, quantization and parallelism
• Profile inference performance to ensure model architecture maximizes hardware efficiency

What You’ll Bring

• Proven experience in scaling and optimizing large AI models, with a strong understanding of performance-related codesign
• Proficiency in Python and a deep understanding of software engineering best practices
• In-depth knowledge of deep learning fundamentals, including optimization techniques, loss functions, and neural network architectures
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Practical experience leveraging GPUs, SIMD instructions, multithreading, or custom accelerators (e.g., TPUs, edge NPUs) for AI model inference and optimization
• Deep understanding with bottlenecks of inference hardware – compute throughput, memory bandwidth, and interconnect
• Specialized experience in one or more of the following domains: model architecture design, quantization-aware-training, model pruning, distillation, and ASIC architecture
• Demonstrated ability to work collaboratively in a cross-functional team environment
• Strong problem-solving skills and the ability to troubleshoot complex system-level issues

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:

• Aetna PPO and HSA plans > 2 medical 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 Account) HSA Contribution when enrolled in the High Deductible Aetna 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
• Employee Assistance Program
• Sick and Vacation time (Flex time for salary 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
$124,000 - $420,000/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.
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process

• Design, train, and evaluate models optimized for edge accelerators
• Focus on improving model quality and training stability with model architecture design
• Conduct scaling laws for model architecture and parallelism-aware compute efficiency
• Work closely with AI engineers, compiler engineers, and hardware engineers to push the frontier of intelligence per watt
• Design novel model architectures and algorithms for scaling and hardware utilization
• Innovate in domains such as sparsity, distillation, quantization and parallelism
• Profile inference performance to ensure model architecture maximizes hardware efficienc