OverviewExperteer OverviewIn this role, you will lead high-fidelity robotics simulations and validation workflows to ensure real-world performance of robotic systems. You'll collaborate across hardware, AI, and simulation teams to build custom sensor models and synthetic data pipelines. You'll advance physics-informed ML and mechanical simulations to improve realism and predictive accuracy at the edge. This position offers the chance to shape state-of-the-art simulation-driven validation for intelligent edge robotics.BenefitsDesign and implement custom sensor models (ToF, RGB-D, LiDAR, IMUs) in simulation platforms (NVIDIA Isaac Sim) using USD integrationApply FEA-based mechanical modelling with tools like Ansys, Comsol, or Abaqus to simulate stress and dynamicsLead sim-to-real alignment through domain randomization, noise modelling, and physics-based constraintsDevelop synthetic data generation workflows for training perception, control, and physics-informed ML modelsCollaborate with AI/ML engineers to integrate simulation outputs into model training pipelinesOversee field validation and on-site testing of robotic platforms and sensors to ensure fidelity and real-world performanceMentor junior engineers and drive adoption of advanced simulation/validation techniquesStay current with robotics simulation advances and sensor techResponsibilitiesPh.D. or M.S. in Robotics, Mechanical Engineering, Computer Science, Physics, or a related field7+ years of robotics simulation, sensor modelling, or mechanical validation experienceDeep expertise in simulation platforms (e.g., Isaac Sim, Gazebo) and sensor modellingStrong proficiency in Python and C++Hands-on experience with FEA tools (Ansys, Comsol, Abaqus)Experience with ML frameworks (PyTorch, TensorFlow) and scientific computing librariesExperience with synthetic data generation and validating against physical benchmarksSolid understanding of sim-to-real challenges and mitigation strategiesQualificationsPh.D. or M.S. in Robotics, Mechanical Engineering, Computer Science, Physics, or a related field7+ years of robotics simulation, sensor modelling, or mechanical validation experienceDeep expertise in simulation platforms (e.g., Isaac Sim, Gazebo) and sensor modellingStrong proficiency in Python and C++Hands-on experience with FEA tools (Ansys, Comsol, Abaqus)Experience with ML frameworks (PyTorch, TensorFlow) and scientific computing librariesProven track record of integrating simulation with real-world robotic systemsExperience with synthetic data generation and validating against physical benchmarksSolid understanding of sim-to-real challenges and mitigation strategies
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