Humanoid

Senior Software Controls Engineer at Humanoid (London, United Kingdom)

Humanoid· London, United Kingdom·

Role details

Work type
Onsite
Employment
Full-Time
Level
Senior

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)

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 are looking for a Software Engineer to join our Control Team in London. You will own how we measure control quality - per robot and across the fleet. Today, judging whether a change made the robot better is still too often an engineer's opinion after a few runs. You will replace that with numbers: reproducible, automated, trusted numbers that say whether a release is better than the last one, whether one robot behaves like another, and whether a fleet is ready for a pilot. This is a software engineering role, not a control design role. You do not need to derive a whole-body controller. You do need real robotics experience, strong engineering discipline, and genuine interest in the physics of what you are measuring - the control engineers bring the theory and will rely on you to tell them the truth about their code.

What You'll Do

Control Quality Metrics

  • Turn qualitative concerns about control quality - smoothness, latency, tracking error, accuracy, and the like - into precise, computable metrics, and build the pipelines that compute them consistently from recorded robot data, simulation runs and live telemetry.
  • Own metric definitions and versioning so a number measured today is comparable with the same number measured six months from now.

Evaluation & Test Infrastructure

  • Develop automated test harnesses that evaluate control releases deterministically - reproducible, run-to-run comparable, free of the hidden state that makes hardware testing unreliable.
  • Wire control evaluation into CI across simulation and hardware-in-the-loop, with pass/fail thresholds so regressions are caught automatically rather than discovered on a customer site.
  • Build the tooling that lets engineers compare controller variants and releases side by side.

Fleet-Level Control Quality

  • Build the per-robot and per-fleet test suites that establish whether each robot meets the expected control performance bar - runnable by other teams without controls support.
  • Track control quality over time and across units - drift, per-robot variation, degradation - and own the path from robot to metric, including the dashboards that make control health legible.

What We're Looking For

  • Robotics experience on real systems - you understand robot data, timing and synchronisation, and the many ways hardware experiments go wrong.
  • Strong Python, plus enough modern C++ to work confidently inside a real-time control codebase and instrument it.
  • Built test automation, evaluation frameworks or benchmarking infrastructure for complex systems - and got other engineers to actually use them.
  • Solid measurement and data analysis judgement: sampling, noise, statistical significance, and knowing when a difference between two runs is real.
  • Experience with robot middleware and data formats (ROS/ROS2, message recording and replay, time sync), CI/CD pipelines and Git-based workflows.

Nice to have:

  • Familiarity with robot kinematics and dynamics, or prior exposure to control systems — enough to hold an informed conversation about what you are measuring.
  • Hardware-in-the-loop test rigs and physical regression testing.
  • Physics simulation environments (MuJoCo, Isaac Sim/Isaac Lab) and sim-to-real validation.
  • Operating or supporting a fleet of robots or other distributed physical devices.
  • Data engineering: pipeline orchestration, time-series databases, large-scale log processing.
  • Release management or quality gates for safety-relevant software.

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