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.
Own low-level control of GENESIS arms and hands.
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.
Own low-level control of GENESIS arms and hands.
Responsibilities
- Design, implement, and tune control algorithms (PID, cascaded loops, LQR, MPC, or nonlinear control) for real robotic hardware
- Model robot dynamics and kinematics to inform controller design and validate performance against real-world behavior
- Take controllers from simulation to physical hardware, anticipating and mitigating the differences between the two
- Debug control instability, timing/latency issues, and hardware-software integration problems end-to-end
- Design and tune state estimation and sensor fusion pipelines that feed closed-loop control
- Collaborate with software, mechanical, and electrical engineers to integrate control systems into the broader robot stack
- Validate control performance through structured testing on hardware, and iterate based on results
- Document control architectures, tuning parameters, and known limitations for the rest of the team
- 3+ years of relevant professional experience
- Deep expertise in control theory (PID, state-space, LQR, MPC, or nonlinear control) and the judgment to choose and design the right approach for a given system
- Proven experience designing controllers for real robotic hardware, not just simulation—including tuning for stability, robustness, and performance under real-world disturbances
- Strong understanding of robot dynamics and kinematics (rigid body dynamics, Lagrangian/Newton-Euler formulations, contact dynamics where relevant)
- Professional experience with ROS/ROS2 and real-time or near-real-time control loops on embedded or industrial hardware
- Real experience in force control.
- Strong C++ and Python skills for control-relevant, performance-critical code
- Experience with state estimation and sensor fusion (Kalman filters, EKF/UKF, or observer design) for closed-loop control
- Comfortable debugging control instability, timing/latency issues, and hardware-software integration problems end-to-end
- Experience with whole-body control, legged locomotion, or highly dexterous/manipulation systems
- Familiarity with trajectory optimization, motion planning, or optimal control frameworks
- Experience with sim-to-real transfer and hardware-in-the-loop testing
- Background integrating learned policies (RL, imitation learning) with classical control stacks
- Familiarity with real-time operating systems or deterministic scheduling (RTOS, PREEMPT_RT)
- Publications, patents, or strong open-source contributions in controls, robotics, or dynamical systems
- 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.