RAI AI Reinforcement Learning Engineer
- Level
- Mid
- Work type
- On-site · Prague
- Visa
- Sponsors visas
Not stated in the posting: salary.
Open. First seen 2 November 2026.
About the role
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. Our R&D and engineering facilities are in Prague, Czech Republic. This role is on-site with our engineering team in the Czech Republic.
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
- Train and evaluate models on REVEL's human-demonstration data
- Build scalable, reproducible training and evaluation pipelines
- Collaborate across the RAI, hardware and data teams
- Push results from research into production on the robot
Requirements
- 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
- 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
Revel Robotics's standard text
Why REVEL
- 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
- The Team: Colleagues from NVIDIA, SpaceX, and Neura Robotics, and founders you work with directly. No layers, no process between you and the decisions
- Your Own Hardware: A top-spec GPU workstation, cluster access, and hands-on time with the robots you're building. Not a software sandbox
- 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
- 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
- Prague, On-Site: Robots need hands, so we work together in our Prague lab. Moving here? We sponsor your work visa and cover relocation
- Lunch, On Us: Complimentary lunch every working day, plus coffee, snacks, and drinks whenever you need a boost
Revel Robotics's standard text
How to apply
- Apply through the link on this posting.
What this role asks for
75% of this description is written for the role. The rest is Revel Robotics's standard text, folded away below.
Compared with Revel Robotics's other open jobs.
The team: AI & Robot Learning
This role is one of 5 open in AI & Robot Learning. 5 were posted in the last 30 days.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (4 of 5), PyTorch (3 of 5), C++ (2 of 5), Machine Learning (2 of 5), ROS (2 of 5)
OTHER ROLES ON THIS TEAM
- sEMG / Biosignal ML Scientist posted Nov 2
- RAI AI Robotics Integration & Deployment Engineer posted Nov 2
- RAI AI Robot Learning Engineer posted Nov 2
- Computer Vision Engineer posted Nov 2
From the team and dates on Revel Robotics's own job board.
Other openings for this role
2 postings for this role in Prague since 3 October 2026, 1 still open. None has been taken down and posted again.
- 2 November 2026 – open (this posting)
- 3 October 2026 – closed 2 November 2026
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