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 Alpha – our rapidly developed humanoid platform now running in real industrial pilots – 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.
#J-18808-Ljbffr…