Вакансии

Location: UK, London Workplace: OnSite 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 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a strong Robotics Learning Engineer to join our Manipulation team based in London. In this role, you will work on teaching our robots to manipulate the world around them. This is a role at the intersection of applied deep learning and robotics, and to be set up for success you need both experience of working with real robot hardware (e.g. identifying issues in control or teleop), and applied deep learning (you don’t have to be an expert on cutting edge neural network techniques, but you should be perfectly capable of curating data, fine-tuning a policy on that data and hypothesising potential mitigations when something doesn’t work). WHAT YOU’LL DO - Post-train manipulation policies via behaviour cloning and RL; own the full loop from data to deployment. - Come up with data preprocessing strategies to improve the quality of collected data. - Work with the simulation team to set up RL training using digital twin, and then iterate on reward and simulation quality to ensure successful transfer to the real world. - Partner with the data collection organization to drive data collection activities for a specific capability: specify what good data looks like, ensure diversity and coverage, and iterate on instructions. - Expand observation and action spaces with new components required to support novel capabilities, and work with the Teleoperations team to expose these components to robot operators. - Partner with Teleoperations and Controls teams to improve motion smoothness and teleoperation experience. - Interface with hardware design team to ensure that manipulation team findings regarding the current generation of hardware are reflected in future designs. WHAT WE'RE LOOKING FOR - 3+ years working on robots (industry or research) with shipped artifacts to show for it. A good understanding of modern teleoperation and low-level control stack. - Experience with neural network post-training. - Familiarity with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training, PyTorch or JAX. Ability to profile & debug numerics and write maintainable research code. - Good familiarity with modern software engineering practices. - Ability to document experiments clearly and communicate trade‑offs crisply. Nice to have: - Experience training VLA models for manipulation (autoregressive, diffusion or flow-matching based). Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks. - Experience applying RL to robotics problems. - Publications at top-tier robotics or deep learning conferences or equivalent open‑source contributions. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of 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.

Location: UK, London Workplace: OnSite 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 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE 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. WHAT YOU’LL DO - 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. WHAT WE'RE LOOKING FOR - 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. WHAT WE OFFER - 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.

Location: US, Boston, MA Workplace: OnSite 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 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We design robots in simulation before building them in hardware. As a Robotics Simulation & RL Engineer, you will help design and validate future generations of our robotic platforms - including bipedal and wheeled systems - using physics simulation and reinforcement learning. You will develop tools to determine whether a robot design can perform real-world tasks before committing to hardware. Your work will directly inform robot architecture, actuator selection, sensor placement, and control strategies. A key responsibility of this role is owning and validating the canonical robot models (URDF and simulation assets) used across simulation and control stacks. WHAT YOU’LL DO - Design and evaluate new robot platforms using physics simulation - Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits - Use reinforcement learning to stress-test robot designs and explore capability limits - Own and maintain URDF models of current and future robot platforms - Maintain the CAD → URDF → simulation pipeline - Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness - Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout - Collaborate with mechanical, control, and perception teams to guide platform design decisions WHAT WE'RE LOOKING FOR - M.Sc http://M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or a related field - Strong foundation in robot kinematics and dynamics - Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar) - Experience with reinforcement learning in robotics or physics-based simulation - Experience working with URDF or similar robot description formats - Strong programming skills in Python and/or C++ - Experience training RL locomotion or manipulation policies Nice to have: - Experience with legged, humanoid, or wheeled robots; - Experience with whole-body control or torque-controlled robots; - Experience with simulation-driven hardware design; - Experience building large-scale RL training pipelines. WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with a 4% employer match. - Equity included–we believe builders should share in what they build. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives. For this role in Massachusetts, the target base salary range is $200K–$300K USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Location: UK, London Workplace: OnSite 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 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London. WHAT YOU’LL DO - Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. - Build and maintain robust CI/CD pipelines for both software and ML workflows. - Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. - Automate deployment, orchestration, and environment management using modern DevOps tooling. - Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. - Proactively detect, troubleshoot, and resolve infrastructure and model performance issues. - Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering. - Document infrastructure, workflows, and operational procedures clearly and thoroughly. WHAT WE'RE LOOKING FOR - Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. - Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. - Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). - Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). - Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. - Ability to design scalable, secure, and observable systems in fast-moving environments. - Strong debugging and problem-solving skills across distributed systems. - Excellent collaboration and communication skills, with experience working in cross-functional teams. - Understanding of security and compliance best practices for both software and ML systems. WHAT WE OFFER - Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. - Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support. - Equity included–we believe builders should share in what they build. - Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.