Senior Autonomy Engineer - Spatial Intelligence

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.

We're hiring a Senior/Staff Autonomy Engineer focused on Spatial Intelligence 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.

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  Architect the spatial intelligence layer that unifies 3D geometry with semantic scene understanding to ensure safe and efficient navigation and locomotion in complex environments

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  Develop advanced 3D spatial reasoning capabilities that provide our robots with long-term persistent spatial memory and a deep contextual awareness of their surroundings.

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  Own the entire perception lifecycle by training large-scale multimodal networks and deploying and integrating them for ultra-low latency performance on edge hardware

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  Bridge the gap between conceptual research and physical reality by implementing state-of-the-art 3D representations that track and interpret the environment state

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  Collaborate with cross-functional teams to bridge the gap between large-scale model training and reliable robot integration.

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  Stay ahead of the field, rapidly evaluate new model architectures, benchmarks, and datasets to guide our embodied AI roadmap.

• Exceptional software engineering skills with a proven track record of shipping complex ML systems into production.

• Strong background in 3D scene understanding and the design of efficient spatial data structures.

• Deep experience in machine learning for vision or embodied AI, ideally with large models (VLMs, transformers, or multi-modal architectures).

• Proficiency in PyTorch and hands-on experience building, fine-tuning, and deploying large-scale ML systems.

• High-impact individual contributor capable of taking projects from conceptual research to high-performance robot code.

• Comfortable working in a fast-moving, research-driven environment with evolving models, data, and tools.