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.
Develop imitation- and reinforcement-learning methods that turn demonstrations into skills. Our RAI team builds the core intelligence that powers REVEL robots, learning from the force and intent Neural Gambit captures.
Responsibilities
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.
Develop imitation- and reinforcement-learning methods that turn demonstrations into skills. 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
- 3+ years of relevant professional experience
- Having modified robot-learning models and taken them from training through on-robot deployment, inference, testing, and validation—not only used off-the-shelf implementations
- Experience building and shipping robot-learning systems on real robots, not only in simulation
- Experience with one or more of the following: behavior cloning, imitation learning, VLAs, VLMs, Transformers, Diffusion Policies, or world models
- Proficient in Python and/or C++ and deep-learning frameworks such as PyTorch for building training pipelines, fine-tuning models, and developing robot-facing code
- Comfortable designing experiments, diagnosing failures, and iterating quickly on physical systems
- Experience using reinforcement learning approaches—such as PPO, SAC, offline RL, or RL fine-tuning—to improve learned robot behaviors
- Track record of deploying learning-based manipulation systems on commercial or production robots, not only demos
- Prior work with humanoids or other highly dexterous robotic platforms
- Publication record in robot learning, manipulation, or embodied AI
- 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
- Equity for Key Roles: For select positions, meaningful stock options mean you're not just working here, you own a piece of the outcome
- Salary and Quarterly Bonus: Strong base pay plus a quarterly bonus, in a city where it goes further
- 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
- 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
- Prague, On-Site: Robots need hands, so we work together in our Prague lab. Moving here? We sponsor your work visa and cover relocation
- Health and Fitness: Multisport card (from December 2026), extra paid sick days, and an employer pension contribution
- Lunch, On Us: Complimentary lunch every working day, plus coffee, snacks and drinks whenever you need a boost
- Apply through the link on this posting. Include a short description of an environment you administered or took over: its size, what you changed about how access or devices were managed, and what you would do differently now.