About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X .

Analog Devices’ Edge AI team is on a mission to redefine how machines perceive and interact with the world. We’re building real-time, intelligent systems that combine world-class sensor technology with cutting-edge AI — at the Edge, where milliseconds matter.

We are seeking a Principal AI/ML Robotics Simulation Engineer to contribute to the development of high-fidelity simulations and real-world validation workflows for robotic systems, including fixed-arm robots and humanoids. This role blends expertise in sensor simulation, mechanical modelling, and AI-driven data workflows to ensure our systems perform reliably in both virtual and physical environments.

You will work closely with hardware, AI, and simulation teams to design sensor models, generate synthetic datasets, and validate simulation assets against real-world data. You will also support the development of physics-informed machine learning models and mechanical simulations using FEA tools.

Responsibilities

• Sensor Simulation: Implement and refine sensor models (e.g., ToF, RGB-D, LiDAR, IMUs) in platforms such as NVIDIA Isaac Sim, using USD and ROS/ROS2 for integration.
• Mechanical Simulation & FEA: Apply FEA techniques to simulate mechanical behaviour of robotic components using tools like Ansys, Comsol, or Abaqus.
• Sim-to-Real Validation: Support efforts to reduce the sim-to-real gap through domain randomization, noise modelling, and physics-based constraints.
• Synthetic Data Generation: Develop simulation workflows to produce synthetic datasets for AI model training and validation.
• ML Collaboration: Work with AI/ML engineers to integrate simulation outputs into training pipelines, especially for physics-informed models.

Qualifications

• M.S. or Ph.D. in Robotics, Mechanical Engineering, Computer Science, Physics, or a related field.
• 10+ years of experience in robotics simulation, sensor modelling, or mechanical validation.
• Proficiency in Python, C++, and ROS/ROS2.
• Experience with simulation platforms (e.g., Isaac Sim, Gazebo) and FEA tools (e.g., Ansys, Comsol, Abaqus).
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and scientific computing libraries.
• Understanding of sim-to-real challenges and validation tech

Bonus Experience

• Contributions to open-source simulation or FEA frameworks.
• Experience with sensor hardware calibration and signal processing.
• Exposure to physics-informed ML or reinforcement learning in robotics.

• Experience generating synthetic data for AI model training.

Why Join Us?

Join ADI’s Edge AI team to help create truly intelligent edge systems — where sensing, learning, and acting happen in real time. You’ll work in a fast-paced, collaborative environment, solving hard problems with people who care about impact, reliability, and real-world performance.

#LI-BF1

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.