Staff AI/ML Simulation Engineer

About the role

Analog Devices' Physical Intelligence organization is developing simulation, synthetic data and AI technologies that combine semiconductor and sensor expertise with machine learning and physics-based modelling. It is looking for a Staff AI/ML Simulation Engineer in Limerick to build and improve simulation and synthetic data capabilities across robotics, sensor simulation, signal-chain simulation, perception simulation and audio simulation. The role works with hardware, AI and simulation engineers to bring simulated and real-world performance closer together.

Key responsibilities

• Design and implement physics-informed machine learning models for simulation, balancing physical accuracy, realism and computational efficiency.
• Develop and optimize simulation workflows combining physics-based modelling with data-driven approaches across sensors, signal chains, robotics, perception and other physical systems.
• Build simulation and synthetic data capabilities for robotics, robotic cognition, ToF, RGB-D, LiDAR, IMUs, audio, signal chains and AI perception systems.
• Collaborate with hardware, AI and simulation engineers to integrate simulation and synthetic data into real-world engineering and AI workflows.
• Apply techniques such as noise modelling, domain randomization, surrogate modelling, physics-based constraints and system identification to reduce the simulation-to-reality gap.
• Validate simulation models against real-world measurements and system behaviour.
• Stay current with PIML, synthetic data and simulation advances and contribute to their adoption in the team.
• Use platforms such as NVIDIA Isaac Sim, ROS/ROS2, USD and scientific computing frameworks where relevant.

Required profile

• M.Sc. or Ph.D. in Physics, Robotics, Computer Science, Electrical Engineering, Applied Mathematics or a related field.
• 5+ years of experience in simulation, machine learning, physical modelling or related engineering, with hands-on physics-based or physics-informed modelling.
• Demonstrated experience developing and deploying physics-informed, hybrid physics/ML or data-driven models for simulation.
• Experience applying simulation to AI development, such as perception, cognition, model training, system validation or sim-to-real transfer.

Required skills

• Advanced ML frameworks such as PyTorch or TensorFlow and scientific computing libraries.
• Proficiency in Python and C++, with experience integrating ML models into engineering or physical systems.
• Strong understanding of physical modelling, sensor physics, signal processing or related fundamentals.
• Experience generating synthetic data and validating simulation models against real-world data.
• Bonus: open-source contributions, publications, familiarity with sensor hardware design, NVIDIA Isaac Sim, Ansys Workbench or COMSOL, and robotics or audio simulation.