At a glanceSummarised by Seekless from the posting.
Must have5
3+ years of relevant professional experience
Track record of building and training RL policies such as PPO, SAC, or offline RL, with a deep understanding of how they work—not just how to call them
Experience applying RL to robotics or physical-system control, including personally deploying and validating RL policies on real hardware
Strong understanding of sim-to-real transfer, including domain randomization, system identification, latency, actuator dynamics, and common transfer failure modes
Comfortable using physics simulators such as Isaac Lab, MuJoCo, or equivalent to train and stress-test policies
Nice to have5
Locomotion or legged-robot RL experience
Understanding of robot dynamics, control theory, or whole-body control
Exposure to VLAs or other foundation models applied to robotics
Experience with offline RL, imitation learning, or approaches combining demonstrations with interaction
Publications or strong open-source work in RL, ML, or robotics
Skills
PPO
SAC
offline RL
Isaac Lab
MuJoCo
VLA
foundation models
Benefits
Unlimited PTO
Relocation assistance
Visa sponsorship
Meal benefit
Free lunch
About REVEL
REVEL is an AI robotics company developing physical intelligence for general-purpose humanoid robots. We capture the force, dexterity and intent of human work with our Neural Gambit wearable, and use it to train RAI, the intelligence that powers our robots. REVEL is headquartered in Palo Alto, California, with R&D and engineering facilities in Prague and Hradec Králové, Czech Republic. This role is on-site with our engineering team in the Czech Republic.
About the role
Design RL and post-training methods to make policies robust and reliable. Our RAI team builds the core intelligence that powers REVEL robots, learning from the force and intent Neural Gambit captures.
Responsibilities
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Train and evaluate models on REVEL’s human-demonstration data
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Build scalable, reproducible training and evaluation pipelines
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Collaborate across the RAI, hardware and data teams
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Push results from research into production on the robot
Requirements
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3+ years of relevant professional experience
•
Track record of building and training RL policies such as PPO, SAC, or offline RL, with a deep understanding of how they work—not just how to call them
•
Experience applying RL to robotics or physical-system control, including personally deploying and validating RL policies on real hardwaree
•
Strong understanding of sim-to-real transfer, including domain randomization, system identification, latency, actuator dynamics, and common transfer failure modes
•
Comfortable using physics simulators such as Isaac Lab, MuJoCo, or equivalent to train and stress-test policies
Bonus qualifications
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Locomotion or legged-robot RL experience
•
Understanding of robot dynamics, control theory, or whole-body control
•
Exposure to VLAs or other foundation models applied to robotics
•
Experience with offline RL, imitation learning, or approaches combining demonstrations with interaction
•
Publications or strong open-source work in RL, ML, or robotics
Why REVEL
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Work That Ships: We capture how skilled humans work, their force, touch, and judgment, and our robots do the work. You put robots on a paying customer’s floor, not in a demo loop
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The Team: Colleagues from NVIDIA, SpaceX, and Neura Robotics, and founders you work with directly. No layers, no process between you and the decisions
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Your Own Hardware: A top-spec GPU workstation, cluster access, and hands-on time with the robots you’re building. Not a software sandbox
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Keep Learning: Conference budget for select roles (GTC, CoRL, ICRA), and room to publish and contribute to open source where our IP allows
What we offer
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Unlimited Paid Time Off: Real flexibility to take time away when you need it. We trust our people to own their work, their time, and their results
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Prague, On-Site: Robots need hands, so we work together in our Prague lab. Moving here? We sponsor your work visa and cover relocation
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Lunch, On Us: Complimentary lunch every working day, plus coffee, snacks, and drinks whenever you need a boost