Neural Simulation ML Software Engineer, Optimus

The Optimus Simulation team is at the forefront of advancing humanoid robotics by building a high-fidelity virtual world where Optimus can safely learn, adapt, and improve. Our mission is to recreate the complexities of the real world in simulation, enabling scalable testing, rapid iteration, and accelerated development of the Optimus autonomy stack. We design and deploy cutting-edge simulation systems that blend accurate physics modeling, photorealistic rendering, and intelligent virtual agents, creating environments that challenge Optimus in the same way the physical world would. These simulations allow us to rigorously evaluate behavior, uncover edge cases, and drive continuous improvements in autonomy and decision-making.
As a member of this team, you will play a pivotal role in shaping the future of humanoid robotics. Your contributions will directly accelerate Optimus' ability to operate effectively in real-world environments by closing the gap between simulation and reality. We are looking for passionate engineers who are excited to push the boundaries of world modeling, neural simulation, and sim-to-real transfer, building systems that will define the next generation of autonomous humanoid robots.

Responsibilities

• Research, implement, and integrate the latest advancements in neural rendering, generative world models, and physics-based simulation
• Collaborate with Simulation and AI Engineers to design, build, and refine neural-based simulation systems
• Develop and maintain data pipelines, tools, and infrastructure to support large-scale model training, validation, and deployment
• Drive innovation in sim-to-real strategies to ensure Optimus performs reliably across both virtual and real-world environments
• Partner cross-functionally with hardware, perception, and autonomy teams to align simulation capabilities with real-world use cases

Requirements

• Hands-on experience training and deploying diffusion models, autoregressive models, or other advanced machine learning architectures
• Strong background in world models, with expertise in sim-to-real transfer, or deep knowledge of physics engines and physical system modeling
• Proficiency in Python and PyTorch, with a proven ability to write clean, scalable, and efficient code
• Solid foundation in mathematics, including linear algebra, numerical methods, probability, and optimization techniques
• Proficiency with Linux-based development environments and version control systems such as Git
• Ability to research, implement, and adapt cutting-edge techniques from academic and industry sources into practical, production-ready solutions

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
$132,000 - $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.