Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we’re growing the team to take it even further.
We are seeking a Teleoperation Control Engineer to help build the systems that let human operators safely, confidently, and precisely control advanced robots. This role sits at the intersection of robot control, real-time software, operator UX, hardware integration, and human-in-the-loop workflows.
You will develop the core teleoperation capability that enables operators to guide, recover, teach, and improve robot behavior in real time. That includes intuitive control mappings, reliable command pipelines, clear operator feedback, high-quality data capture, and safeguards for safe use around real hardware.
We are open to strong candidates from junior through staff level. The key traits are hands-on robotics ability, strong engineering judgment, care for software quality, and a product-minded instinct for making complex robot systems intuitive for operators.
Develop teleoperation capabilities for controlling robots across manipulation, mobility, and loco-manipulation tasks.
Design intuitive operator experiences, including input mappings, visualizations, feedback loops, recovery flows, and workflows that reduce cognitive load and improve operator confidence.
Integrate input devices such as VR controllers, gloves, haptic devices, motion capture systems, and custom operator stations into the robot software stack.
Translate noisy, high-frequency human input into smooth, stable, physically feasible robot commands with predictable behavior.
Build robust teleoperation infrastructure for real-time data streaming, calibration, replay, debugging, logging, operator training, and high-quality demonstration capture.
Develop shared-autonomy and assistive-control features that blend human intent with robot capability to improve precision, safety, and ease of use.
Create safe operating boundaries, limiters, alerts, emergency/recovery flows, and clear state feedback so robot operators can use teleoperation safely.
Define and improve quality metrics for teleoperation systems, including latency, reliability, observability, operator success rate, demonstration quality, and failure modes.
Stress-test teleoperation systems on real hardware and in simulation, then drive reliability improvements based on operator feedback and observed failures.
Work closely with controls, manipulation, hardware, and operations teams to ensure teleoperation requirements shape robot design and field workflows.
Strong robotics fundamentals, including kinematics, coordinate frames, control interfaces, state estimation basics, and real-time system behavior.
Experience building a subset of the following: teleoperation systems, operator UIs, shared-autonomy tools, human-robot interfaces, or robot learning data-collection pipelines.
Ability to write reliable software in C++ and/or Python, with experience in ROS/ROS2, real-time data streaming, or robotic middleware.
Good intuition for human-in-the-loop systems: how operators perceive robot state, issue commands, recover from errors, and build trust.
A quality mindset: clean abstractions, testing, logging, observability, performance tuning, and tools that remain usable under pressure.
Strong debugging skills across the stack, from operator input devices to robot motion, sensors, networking, and hardware behavior.
Comfort iterating quickly on real robots, learning from operator feedback, and turning prototypes into robust capabilities.
Clear communication and collaboration with cross-functional teams.
Nice to have:
Hands-on experience building or debugging software for real robotic hardware, ideally in manipulation, mobile manipulation, humanoids, or dexterous systems.
Experience designing safe workflows for hardware-facing systems where latency, instability, poor feedback, or misuse can create operational risk.
Experience collecting high-quality demonstrations for imitation learning, behavior cloning, or other robot learning workflows.
Exposure to intent inference, haptics, force feedback, motion capture, VR/AR interfaces, or custom control devices.
A product-minded approach to robotics: caring not only that the robot moves, but that control is intuitive, safe, reliable, and pleasant for operators to use.
Competitive equity: stock options with meaningful upside as we scale.
30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).
Private healthcare, including virtual and in-person care.
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
Free daily breakfast, catered lunch, and snacks in-office.
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
