Overview
We are developing a next-generation humanoid robot using a simulation-first, capability-driven approach to hardware design. As a Capability Simulation & Control Engineer, your mission is to analyze and characterize the limits of our robotic platforms - before they are built. You will sit at the intersection of simulation, control, and hardware design, enabling rapid iteration cycles by ensuring we understand the physical and algorithmic feasibility of each design decision.
Responsibilities
* Capability Evaluation & Simulation: Develop tools and pipelines to analyze and visualize platform capabilities (e.g., kinematic reach, manipulability maps, dynamic feasibility, joint torque-speed curves).
* Integrate dynamic and quasi-static evaluations of locomotion, manipulation, and perception effectiveness into the simulation loop.
* Incorporate model-based and learning-based methods to evaluate adaptive capabilities under uncertainty.
* Hardware Design Feedback Loop: Provide actionable quantitative insights to inform joint placement, limb proportions, mass distribution, sensor positioning, actuator sizing, and other HW design variables.
* Work closely with mechanical engineers, control developers, and perception experts to co-design simulation tasks that expose key tradeoffs and performance bottlenecks.
* Design and implement reusable test scenarios for various hardware configurations and use cases.
* Automate performance reporting and limit detection in the context of control performance, perception accuracy, and stability.
* Model Fidelity & Integration: Ensure that models used for capability analysis reflect sufficient physical realism without slowing iteration cycles.
* Collaborate with simulation experts to incorporate contact models, compliance, and actuator characteristics into the testing loop.
* Design Exploration: Support rapid evaluation of alternate hardware morphologies by stress-testing capabilities through scripted benchmarks or learned behaviors.
* Develop visual and quantitative design-space exploration tools to help prioritize tradeoffs across metrics (e.g., power consumption vs workspace).
Requirements
* M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control Systems, or a related field.
* Solid foundation in robot kinematics, dynamics, and control.
* Proficient in simulation environments such as MuJoCo and Isaac Sim, or custom tools.
* Experience evaluating or optimizing robotic systems for capability limits (reach, manipulability, torque-speed, dynamic stability).
* Familiarity with optimization tools and version control for collaborative pipelines.
* Strong software skills (Python and/or C++; experience with ROS or similar frameworks).
* Ability to communicate technical results to multidisciplinary teams and influence design decisions.
Nice-to-Have
* Familiarity with whole-body control, redundancy resolution, or torque-controlled platforms.
* Experience with optimization and design-space exploration.
* Exposure to hardware-in-the-loop simulation or perceptual simulation.
* Hands-on experience with humanoid or bipedal platforms, including torque-controlled systems.
What We Offer
* Competitive salary plus participation in our Stock Option Plan
* Paid vacation and travel opportunities to our London, Vancouver, and Boston offices
* Office perks: free breakfasts, lunches, snacks, and regular team events
* Freedom to influence the product and own key initiatives
* Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics
* Startup culture prioritising speed, transparency, and minimal bureaucracy
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