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Reinforcement Learning Engineer, Policy, Digital Optimus
Accepting applicationsTesla · Palo Alto, CA
Full-Time Entry AIPythonSicaiasic
Posted
6d ago
Category
Test
Experience
Entry
Country
United States
What To Expect
As a Reinforcement Learning Engineer on the Policy team at Digital Optimus, you will design and scale post-training systems to make our computer-use agents more reliable, capable, and autonomous. You will build RL pipelines (PPO, GRPO, and hybrids) that turn real agent interaction data — screen observations, actions, and outcomes — into continuous policy improvements.
This role blends strong RL expertise with production engineering to bridge impressive demos and reliable digital agents.
What You'll Do
Lead large-scale post-training runs using PPO, GRPO, and related methods on agent trajectories
Design evaluation systems, benchmarks, and scorers to diagnose and fix policy issues in long-horizon tasks
Build reward signals and feedback loops combining outcomes, process supervision, safety, and human feedback
Run and optimize distributed RL training pipelines at scale
Iterate quickly on training data, reward shaping, and multimodal policies
Collaborate with Harness, Vision, and Infrastructure teams to deploy improved policies
What You'll Bring
Strong hands-on experience with RL post-training for LLMs/VLMs (PPO, GRPO, RLHF, or similar)
Experience building evaluation frameworks and turning insights into training improvements
Proficiency with distributed training systems (DeepSpeed, FSDP, Ray) and large-scale data pipelines
Solid software engineering skills (Python) and intuition for production ML systems
Understanding of long-horizon RL challenges: credit assignment, reward hacking, and training stability
Background in computer-use agents, robotics RL, or screen/GUI interaction is a plus
Experience with large-scale RL on real user data is a plus
Contributions to RLHF, RLAIF, or GRPO implementations is a plus
Benefits
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
Expected Compensation
$124,000 - $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.
, Tesla
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As a Reinforcement Learning Engineer on the Policy team at Digital Optimus, you will design and scale post-training systems to make our computer-use agents more reliable, capable, and autonomous. You will build RL pipelines (PPO, GRPO, and hybrids) that turn real agent interaction data — screen observations, actions, and outcomes — into continuous policy improvements.
This role blends strong RL expertise with production engineering to bridge impressive demos and reliable digital agents.
What You'll Do
Lead large-scale post-training runs using PPO, GRPO, and related methods on agent trajectories
Design evaluation systems, benchmarks, and scorers to diagnose and fix policy issues in long-horizon tasks
Build reward signals and feedback loops combining outcomes, process supervision, safety, and human feedback
Run and optimize distributed RL training pipelines at scale
Iterate quickly on training data, reward shaping, and multimodal policies
Collaborate with Harness, Vision, and Infrastructure teams to deploy improved policies
What You'll Bring
Strong hands-on experience with RL post-training for LLMs/VLMs (PPO, GRPO, RLHF, or similar)
Experience building evaluation frameworks and turning insights into training improvements
Proficiency with distributed training systems (DeepSpeed, FSDP, Ray) and large-scale data pipelines
Solid software engineering skills (Python) and intuition for production ML systems
Understanding of long-horizon RL challenges: credit assignment, reward hacking, and training stability
Background in computer-use agents, robotics RL, or screen/GUI interaction is a plus
Experience with large-scale RL on real user data is a plus
Contributions to RLHF, RLAIF, or GRPO implementations is a plus
Benefits
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
Expected Compensation
$124,000 - $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.
, Tesla
Show more Show less