About this role
<h1>Principal Robotics AI Engineer (Loco-Manipulation & Whole-Body Control)</h1> <h1>Job Overview</h1> <p>AI.DA STC (Strategic Technology Centre)'s NEAR (Next-gen Edge AI & Robotics) Lab is building a deep ground robotics research capability. We're looking for a Principal Engineer to anchor our loco-manipulation and whole-body control work. This involves making legged platforms reliable for contact-rich manipulation and cooperative tasks in unstructured environments.</p> <p>This is an engineering-first role with active research participation. The primary measure of impact is shipping working systems on real hardware. Publications happen alongside that work, co-authored with academic collaborators and lab engineers when the technical contribution warrants it. You'll join a small ground robotics team, partner with our embodied AI lead, and work alongside academic collaborators, startups and robotics vendors in Singapore and abroad.</p> <p>This role reports initially to the Lab Director. As the ground robotics team grows over the next 12 months, the reporting line will evolve; we'll be transparent about this trajectory throughout the hiring process.</p> <h1>Loco-Manipulation & Whole-Body Control</h1> <ul> <li><strong>Whole-Body Control & RL for Legged Systems:</strong> Design and ship the WBC stack for our legged platforms; coupled base-arm controllers, contact-aware control, and hybrid policies combining RL with model-based control. Sim-to-real for contact-rich tasks, training in Isaac Sim or MuJoCo, deployment onto edge compute.</li> <li><strong>Contact-Rich Manipulation:</strong> Build manipulation policies for tasks where balance, contact force, and locomotion are coupled: door opening, valve turning, payload transport, debris handling. Force and impedance control on real hardware.</li> <li><strong>Cross-Embodiment Transfer:</strong> Lead the lab's work transferring policies across embodiments: bimanual demonstrations to single-arm quadrupeds, quadruped manipulation to humanoid.</li> <li><strong>Technical Direction & Mentorship:</strong> Set the technical direction for the ground robotics manipulation stack and develop more junior engineers through code review and direct technical mentorship.</li> </ul> <h1>Wider Scope</h1> <ul> <li><strong>Locomotion & Autonomous Navigation:</strong> Partner with the embodied AI lead on rugged-terrain locomotion and on integrating loco-manipulation with the autonomous navigation stack.</li> <li><strong>Multi-Robot & Cooperative Manipulation:</strong> Contribute to multi-robot manipulation as the lab scales from single-arm to distributed bimanual systems and cooperative payload transport, including the deployment infrastructure (ROS 2 multi-robot architecture, RMF, mesh networking) that makes multi-robot field trials work.</li> </ul> <h1>Required Qualifications</h1> <ul> <li><strong>Education & Experience:</strong> PhD strongly preferred in Robotics, Mechanical Engineering, Computer Science, Electrical Engineering, or related field; or Master's with strong industry-research track record. 8+ years of post-graduate experience in legged robotics, mobile manipulation, or whole-body control. Shipped systems and field deployment weighted as heavily as academic credentials.</li> <li><strong>Whole-Body Control & RL Depth:</strong> Direct implementation experience with WBC (classical MPC/QP, learned, or hybrid) and hands-on deployment of RL policies onto real legged platforms, with demonstrated ability to close the sim-to-real gap on hardware.</li> <li><strong>Contact-Rich Manipulation:</strong> Hands-on experience with force, impedance, or admittance control on real arms, ideally on mobile bases.</li> <li><strong>Real-Robot Track Record:</strong> Multi-year pattern of taking engineering problems to working solutions on hardware: bring-up, commissioning, field debugging, on-robot diagnostics. Demonstrated ability to adapt open-source robotics repositories to real platforms and make them survive field conditions.</li> <li><strong>ROS 2 & Multi-Robot Systems:</strong> Strong working knowledge of ROS 2 including multi-robot architecture, DDS configuration, and real-world debugging of distributed systems. Familiarity with Open-RMF or equivalent. Direct experience deploying multi-robot systems on real hardware.</li> <li><strong>Software:</strong> Strong C++17/20 and Python in Linux environments. Fluent with modern AI coding assistants and clear-headed about when to use them.</li> </ul> <h1>Preferred Qualifications</h1> <ul> <li><strong>Industry Research Experience:</strong> Prior work at industrial research labs that ship to hardware, e.g. NVIDIA Robotics, Toyota Research Institute, or equivalents.</li> <li><strong>Advanced Manipulation or humanoid:</strong> Hands-on work with industrial/research arms (Franka, UR5e, uFactory), or with humanoid platforms for contact-rich manipulation.</li> <li><strong>Collective & Cooperative Manipulation:</strong> Prior work on multi-robot cooperative manipulation, collective transport, or coordinated loco-manipulation across multiple legged platforms.</li> <li><strong>World Models & Learned Dynamics:</strong> Exposure to world models or learned dynamics models for manipulation planning and multi-robot coordination.</li> <li><strong>VLA, Foundation Models & Imitation Learning:</strong> Experience deploying VLAs on real robots; familiarity with bimanual imitation-learning pipelines (Mobile ALOHA or equivalent).</li> <li><strong>Tactile Sensing & Simulation Depth:</strong> Prior work with tactile sensors, F/T feedback, or compliant grippers; depth in Isaac Sim, MuJoCo, or Isaac Lab including domain randomisation.</li> <li><strong>Research Output:</strong> Peer-reviewed publication at ICRA, CoRL, RSS, RA-L, or IROS.</li> <li><strong>Field Robotics:</strong> Context in safety-critical, defence-relevant, or extended field-deployed robotics.</li> </ul>