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Humanoid

Staff Robotics Control Engineer - Whole-Body Control (Wheeled Platform)

London
Posted about 21 hours ago
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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 Staff Robotics Control Engineer to join our Control Team in London and lead the evolution of whole-body control for our Wheeled Alpha platform - a humanoid whose whole body spans a wheeled base, torso and two arms, controlled as one coordinated system.

We need genuine depth in classical whole-body control. You should know hierarchical and weighted QP formulations from the inside - not as a library you have called, but as something you have derived, implemented, tuned, profiled and debugged on real hardware under demo pressure. You should have opinions about strict hierarchies versus soft-weighted stacks, regularisation and nullspace behaviour, what to do when a task set becomes infeasible, and how to keep a redundant system clear of singularities without it feeling sluggish. Alongside that depth, you will set technical direction and mentor a strong team of control engineers.

What You'll Do

Whole-Body Control Architecture & Algorithms

  • Lead the evolution of the Wheeled Alpha whole-body controller: task formulation, prioritisation, weighting, constraint handling and solver selection.
  • Coordinate wheeled base, torso and dual-arm motion within a single whole-body formulation, with base motion that tracks commanded targets accurately and stays well-behaved under aggressive commands and long-duration operation.
  • Own the constraint layer - self-collision avoidance, joint and velocity limit guarding, and singularity handling - plus feasibility handling and recovery when the solver fails.
  • Drive the evolution toward predictive formulations: evaluate and develop MPC-based whole-body control where anticipating dynamics and constraints outperforms instantaneous QP resolution.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Dynamics, Compliance & Payload

  • Own the dynamic models the controller runs on - inertial, gravity and friction modelling, system identification, and online payload estimation - so the robot knows what it is carrying and controls accordingly.
  • Advance compliance and force behaviour - impedance, admittance and force control that stays compliant at contact - and extend payload capability without sacrificing either.
  • Own stability-aware behaviour under changing payload and dynamic motion.

Safety Integration

  • Make whole-body control a first-class citizen of the safety architecture: the controller must accept and honour requests from dedicated safety compute - velocity capping, controlled deceleration, constrained operating envelopes - provably and without degrading motion quality.
  • Co-own the controls-to-safety interface with the safety team, and design control behaviour so that safety interventions are graceful rather than abrupt.

Technical Leadership

  • Define the performance metrics for whole-body control and insist on deterministic, reproducible evaluation of every change, in simulation and on hardware.
  • Mentor control engineers on optimisation-based control, numerical robustness and hardware debugging; act as reviewer of record for the most consequential changes.
  • Work with hardware teams so control constraints and mechanical design decisions stay coherent.

What We're Looking For

  • Deep, demonstrable expertise in optimisation-based whole-body control: hierarchical and weighted QP formulations, task prioritisation, constraint handling, and the numerical realities of solving them inside a real-time loop.
  • Strong command of the classical WBC toolkit - operational space and task-space control, inverse dynamics and IK formulations, redundancy resolution, nullspace projection, impedance and admittance control, contact and force control - and working knowledge of MPC formulations for whole-body or mobile-manipulation control.
  • Deployed whole-body controllers on real high-DoF hardware (humanoids, mobile manipulators, dual-arm or legged platforms), including coordinating base and manipulator motion.
  • Practical fluency with QP/NLP solvers and their failure modes: conditioning, infeasibility, warm starting, solve-time budgets, and what to do at the limit.
  • Strong dynamic modelling foundations: rigid body kinematics/dynamics (Jacobians, dynamics formulations, URDF-based modelling), inertial and friction system identification, and payload/external-load estimation.
  • Expert modern C++ for real-time control with Python for analysis and prototyping.
  • Track record of taking control algorithms to production reliability rather than to a paper or a one-off demo, plus demonstrated technical leadership and mentoring.

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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.
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Skills

Whole-Body Control
Quadratic Programming (QP)
Model Predictive Control (MPC)
C++
Python
Inverse Dynamics
Impedance Control
Admittance Control
Rigid Body Kinematics
System Identification
Numerical Optimization
Real-time Control
Robotics Dynamics
Task-space Control
Nullspace Projection
Force Control

Location

London, England, United Kingdom

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