Senior Autonomy Engineer; SLAM & Navigation

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're hiring a Senior Autonomy Engineer (SLAM & Navigation) to join our team. In this role, you will bridge the gap between classical spatial geometry and next-generation AI. You will lead the design and development of robust state estimation, long-term mapping, and localisation loops, with a specific focus on integrating modern machine learning techniques and foundation geometry models into our core navigation stack.

Your work will ensure our robots possess rock-solid spatial awareness and execute highly reliable trajectories over extended deployments in complex, real-world environments.

• Design and scale robust SLAM pipelines that maintain highly accurate localisation and state estimation across dynamic physical spaces.

• Integrate foundation geometry models and modern ML techniques into the localisation loop to enhance traditional spatial tracking, data association, and visual odometry.

• Architect and maintain robust long-term mapping systems that enable robots to autonomously update, manage, and scale spatial maps across changing environments over time.

• Build and scale auto-labeling data pipelines that leverage foundation geometry models to generate high-fidelity spatial ground truth for downstream ML training.

• Bridge classical geometry with deep learning architectures, building hybrid systems that map raw sensor data into globally consistent metric trajectories.

• Deploy and benchmark spatial AI software directly on physical robot hardware, ensuring deterministic, ultra-low latency execution on edge compute.

• Translate cutting‑edge spatial AI research into production reality, continuously evaluating breakthroughs in geometric learning to guide our navigation roadmap.

• Deep expertise in classical SLAM and multi‑view geometry, including extensive hands‑on experience with state estimation, visual/LiDAR odometry, and multi‑sensor fusion.

• Experience handling backend map optimization and solving the unique structural challenges associated with long‑term mapping in large or changing physical environments.

• Practical experience applying modern ML to geometric problems, with exposure to utilizing or adapting newer foundation geometry models.

• Proven ability to build scalable data pipelines or auto‑labeling workflows tailored for geometric and spatial datasets.

• Proficiency in C++ and Python, with a track record of writing clean, highly parallelized, production‑grade algorithmic code.

• Hands‑on experience deploying navigation systems on physical hardware, with a deep understanding of the practical edge constraints of real‑world robotics.

• A research‑to‑production mindset, capable of tearing through the latest CVPR/ICRA papers and figuring out exactly how to make those models run with bulletproof reliability.

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), separate sick leave, and paid bank holidays and 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.

• 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.