Senior Robot Learning Engineer

Analog Devices•Boston, MA

About The Position

Come join Analog Devices (ADI) – a place where Innovation meets Impact. For more than 55 years, Analog Devices has been inventing new breakthrough technologies that transform lives. At ADI you will work alongside the brightest minds to collaborate on solving complex problems that matter from autonomous vehicles, drones and factories to augmented reality and remote healthcare. ADI fosters a culture that focuses on employees through beneficial programs, aligned goals, continuous learning opportunities, and practices that create a more sustainable future. 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, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X). Senior Robot Learning Engineer The Dexterous AI Group (DAG) is looking for Robot Learning Engineers to develop core AI technologies for Analog Devices’ future AI robotics with generality and dexterity, beyond the reach of traditional algorithms and system innovations, with a strong emphasis on bridging simulation and real-world robotic performance.

Requirements

Master’s degree or equivalent experience, Ph.D. is preferred.
3+ years of research experience in robot learning.
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).
Training deep learning models with PyTorch and familiarity with large multi-modal datasets and models.
A track record of relevant publications in top international conferences (RSS, NeuRIPS, ICML, ICLR, CoRL, ICRA, IROS, …)

Nice To Haves

familiarity with foundation models and large language models.
robotics toolkits (e.g., ROS/ROS2, Mujoco, Isaac)
robotic systems and mechanical design

Responsibilities

Contribute the development of advanced learning algorithms for general and dexterous robot using the state-of-the-art techniques.
Create sandbox simulations, deployable implementations, and evaluation frameworks for algorithm performance and robustness.
Contribute to data requirements, data collection setup and procedure, and data curation.
Stay abreast of the latest developments in machine learning and robotics from reputable groups.