Senior Software Controls Engineer

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 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.

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.

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.

• 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.

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.

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