Design and implement custom sensor models (e.g., ToF, RGB-D, LiDAR, IMUs) in simulation platforms.
Apply traditional numerical simulation techniques (e.g., FEA) to model mechanical behaviour of robotic components.
Lead efforts to close the sim-to-real gap in robotics use-cases through domain randomization, noise modelling, and physics-based constraints.
Develop simulation-driven workflows to produce high-quality synthetic datasets for training AI models.
Collaborate with AI/ML engineers to integrate simulation outputs into model training pipelines.
Oversee on-site testing and validation of robotic platforms and sensor arrays.
Stay current with advancements in robotics simulation, sensor technologies, and AI.

Ph.D. or M.S. in Robotics, Mechanical Engineering, Computer Science, Physics, or a related field.
6+ years of experience in robotics simulation, sensor modelling, or mechanical validation.
Deep expertise in simulation platforms (e.g., Isaac Sim, Gazebo) and sensor modelling.
Strong proficiency in Python, C++, and software development best practices.
Hands-on experience with FEA tools such as Ansys, Comsol, or Abaqus.
Experience with advanced ML frameworks (e.g., PyTorch, TensorFlow) and scientific computing libraries.
Proven track record of integrating simulation with real-world robotic systems.
Experience with synthetic data generation and validation against physical benchmarks.
Solid understanding of sim-to-real challenges and mitigation strategies.

Staff Robotics Simulation Engineer, AI/ML Software

Key skills