1X Technologies AS
Research Engineer, Reinforcement Learning
1X Technologies AS, Palo Alto, California, United States, 94306
AI Research Engineer, Reinforcement Learning | AI & Robotics
Location: Palo Alto, CA (on-site)
About 1X We build humanoid robots that work alongside people to solve labor shortages and create abundance.
The Role As a Research Engineer focused on Reinforcement Learning, you will be responsible for teaching NEO new capabilities through RL algorithms. You’ll work across both simulation and real‑world environments to build robust behaviors and deploy them into homes. This role will be instrumental in making our robots safer, more capable, and increasingly versatile.
You Will
Own the full stack of engineering tasks, from data engineering and model architecture to product deployment
Train NEO on a variety of manipulation and locomotion tasks
Collaborate with hardware teams to bridge the sim‑to‑real gap for policies trained in simulation
Partner with controls, QA, and data collection teams to ship RL policies to production
Deploy reinforcement learning‑trained skills into real‑world home environments
Must Have
Strong programming experience in Python and/or C++ with familiarity using build tools such as Bazel
Proficiency with PyTorch
Hands‑on experience with simulation platforms like Isaac Sim or MuJoCo
Experience training reinforcement learning policies, especially for manipulation or locomotion
Ability to collaborate cross‑functionally with hardware, control, data, and QA teams
Demonstrated experience addressing the sim‑to‑real gap
Benefits & Compensation
Salary Range: $180,000 – $250,000 + Equity
Health, dental, and vision insurance
401(k) with company match
Paid time off and holidays
Equal Opportunity Employer 1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, or any other characteristic protected under applicable federal, state, or local law.
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About 1X We build humanoid robots that work alongside people to solve labor shortages and create abundance.
The Role As a Research Engineer focused on Reinforcement Learning, you will be responsible for teaching NEO new capabilities through RL algorithms. You’ll work across both simulation and real‑world environments to build robust behaviors and deploy them into homes. This role will be instrumental in making our robots safer, more capable, and increasingly versatile.
You Will
Own the full stack of engineering tasks, from data engineering and model architecture to product deployment
Train NEO on a variety of manipulation and locomotion tasks
Collaborate with hardware teams to bridge the sim‑to‑real gap for policies trained in simulation
Partner with controls, QA, and data collection teams to ship RL policies to production
Deploy reinforcement learning‑trained skills into real‑world home environments
Must Have
Strong programming experience in Python and/or C++ with familiarity using build tools such as Bazel
Proficiency with PyTorch
Hands‑on experience with simulation platforms like Isaac Sim or MuJoCo
Experience training reinforcement learning policies, especially for manipulation or locomotion
Ability to collaborate cross‑functionally with hardware, control, data, and QA teams
Demonstrated experience addressing the sim‑to‑real gap
Benefits & Compensation
Salary Range: $180,000 – $250,000 + Equity
Health, dental, and vision insurance
401(k) with company match
Paid time off and holidays
Equal Opportunity Employer 1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, or any other characteristic protected under applicable federal, state, or local law.
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