
Senior Autonomy Engineer - SLAM & Navigation at Humanoid (London, United Kingdom)
Humanoid· London, United Kingdom·
Role details
23 Days Of Annual Leave · Sick Leave · Paid Bank Holidays · Company Holidays · Fully Funded Private Healthcare · Mental Health Support · Pension Scheme With 8% Contribution · Free Daily Breakfast
Humanoid at a glance
Humanoid builds commercially scalable, safe humanoid robots to automate labor-intensive industrial tasks in warehousing, logistics, and manufacturing.
Designs and builds general-purpose humanoid robots (the HMND 01 platform) that automate physical industrial tasks like goods handling, picking and packing, and kitting, orchestrated by an in-house AI fleet framework called KinetIQ.
Approximately $30M self-funded by founder Artem Sokolov; a ~$200M Series A was in talks as of early 2026 (not closed) raised · latest: Series A (in talks, ~$200M, no valuation set) as of February 2026 · backed by Artem Sokolov (founder, sole shareholder)
Summary
Lead the design and development of robust state estimation, long-term mapping, and localization loops for humanoid robots. Integrate modern machine learning and foundation geometry models into the core navigation stack to ensure reliable spatial awareness in real-world environments.
Job description
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.
- 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.
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.
Why work at Humanoid
- High-growth environment: Company grew headcount by 139% in a single year, indicating rapid scaling and opportunity for career advancement. 65+ open roles suggest strong hiring momentum.
- Talent from top robotics firms: Team includes alumni from Boston Dynamics, Sanctuary AI, Dyson, Ocado Technology, Arrival, Wayve, and others — offering a deep learning and collaboration environment.
- Technical focus: Engineering and technical roles represent 38% of the workforce, with senior-level hires at 23% of the team. The company emphasizes hardware, AI, machine learning, and control systems.
- Mission-driven: Clear purpose to automate undesirable, unsafe, and repetitive work — appealing to candidates who want to make a tangible societal impact.
- Global presence: Offices in London (HQ), Cambridge (USA), and Burnaby (Canada), plus operations in 16 countries — offering potential for international mobility and remote collaboration.
- Innovation culture: Described as a place where engineers and researchers “move from demo to deployment” and “not just in the lab.” The CTO emphasizes building systems that perform in the real world from day one.
- Office/Hybrid policy: Not explicitly stated, but the company has physical offices in three countries and a distributed team across 16 nations — likely supports hybrid/remote with in-office collaboration for engineering roles.