Staff Robot Learning Engineer

Analog Devices•San Jose, CA

1d•$150,978 - $218,624•Onsite

About The Position

Analog Devices (ADI) is launching an exciting new initiative — the Emerging Tech Hub — a physical space where customers, partners, and academic collaborators can rapidly prototype solutions tailored to their unique challenges. We are seeking an experienced Robot Learning Engineer to develop advanced robotic software frameworks that enable core AI innovations in robotics. The ideal candidate will design and implement state-of-the-art learning-based algorithms and robotic systems that go beyond the limitations of traditional approaches. This role will focus on bridging the gap between simulation and real-world deployment, enabling robust, scalable, and high-performance robotic capabilities.

Requirements

Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or a related technical field, Ph.D. is preferred.
3+ years of professional experience in robot learning.
Experience with robotic middleware platforms, especially ROS/ROS2.
Proven hands-on experience developing simulation environments and synthetic data generation pipelines using NVIDIA Isaac Sim or MuJoCo
Strong background in machine learning and robotics, and experience in: Reinforcement Learning and Imitation Learning for manipulation.
Planning and control algorithms (e.g., A*, MPC).
Optimization techniques (e.g., linear/nonlinear optimization).
Strong AI/ML Fundamentals: Familiarity with machine learning concepts, especially in the context of robot perception and control (e.g., PyTorch, TensorFlow).
A track record of relevant publications in top international conferences (RSS, NeuRIPS, ICML, ICLR, CoRL, ICRA, IROS)

Responsibilities

Develop and implement state-of-the-art AI algorithms for robotic manipulation, motion planning, perception and control.
Integrate and calibrate perception systems (e.g., cameras, LiDAR, tactile sensors) with robotic platforms to enable enhanced task-awareness.
Create simulation environments, deployable implementations, and evaluation frameworks to assess algorithm performance, scalability, and robustness.
Establish data requirements, design data collection workflows, and support data collection, and curation for AI model development.
Collaborate with AI researchers to translate cutting-edge algorithms into robust software implementations.
Stay updated with the latest advancements in robotics software and AI to continuously enhance the team’s capabilities.