A venture backed physical AI and robotics firm is transforming construction by automating building manufacturing using modular, containerised robotic production cells. With commercial systems deploying across international markets, the firm operates out of an expansive London R&D and demonstration facility.
Key Responsibilities
Own and evolve physics based simulation environments built in NVIDIA Isaac Sim to model modular robotic production cells.
Establish robust asset pipelines translating engineering geometry and CAD models directly into USD.
Tune dynamics parameters including joint limits, stiffness, damping, contacts, and friction, diagnosing deviations between simulated and live machines.
Interface simulation setups with core robotics software through standard ROS 2 abstractions.
Create virtual test suites and automated CI scenarios to validate failure conditions, edge cases, and continuous hardware changes.
Bridge sim to real discrepancies that impact engineering decisions, maintaining tight alignment between digital twins and deployed systems.
Structure simulation runs into usable datasets and generate synthetic data with domain randomisation to assist computer vision development.
Substantial hands‑on experience building and maintaining robotics simulation environments in NVIDIA Isaac Sim.
Deep grounding in simulation physics, including mechanics, joint tuning, contacts, and dynamical stability.
Strong Python programming skills alongside everyday familiarity with Linux, Docker, and Git.
Practical experience linking simulation setups to operational robotics software using ROS 2.
Experience working with engineering CAD geometry and 3D asset conversion in robotics or automation settings.
Strong engineering judgement to balance simulation fidelity against computational complexity and usability.
Excellent cross-disciplinary collaboration skills across robotics software, controls, and mechanical engineering teams.
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