Humanoid

Senior Autonomy Engineer - SLAM & Navigation at Humanoid (London, United Kingdom)

Humanoid· London, United Kingdom·

Role details

Work type
Onsite
Employment
Full-Time
Level
Senior
Skills
C++PythonSLAMMulti-view geometryState estimationVisual odometryLiDAR odometryMulti-sensor fusionMap optimizationMachine LearningFoundation geometry modelsData pipelines
Benefits

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.

Application questions