Senior Autonomy Engineer - SLAM & Navigation

About the role

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 Autonomy Engineer focused on 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.

WHAT YOU'LL DO

- 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.

WHAT WE'RE LOOKING FOR

- 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.