Principal AI/ML Engineer (Robotics)

We are looking for a Principal Engineer with deep domain expertise in robot policies, task planning, computer vision and decision-making under uncertainty to lead the development of real-world expert and generalist robot policies. Your work will drive how autonomous systems reason about goals, decompose tasks, and adapt in dynamic environments.

You will join a high-impact team developing foundational components for ADI’s next wave of robotics solutions. This is a hands-on leadership role for someone who thrives on solving open-ended challenges, defining technical roadmaps, and mentoring other engineers.

Responsibilities

Lead the design and deployment of expert and generalist policies that enable industrial targeted tasksets to be enacted.

Drive the design of task policies using techniques such as hierarchical planning, reinforcement learning, or hybrid methods.

Develop real-world and simulation-based datasets for benchmarking and validation; guide sensor selection and system integration.

Collaborate cross-functionally with embedded, hardware, and systems engineers to bring scalable solutions from research to production.

Stay current with the state of the art in robotics, Edge AI, and self-supervised learning — and guide the team in adopting innovative technologies.

Contribute to the broader AI platform architecture, CI/CD pipelines, and MLOps practices.

Qualifications

10+ years of experience in robotics, computer vision, control theory or AI; with 3+ years in a technical leadership role.

M.S. or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field.

Demonstrated expertise in at least one of the following:

Task and motion planning

Policy learning methods

Robot foundation models

Decision making under uncertainty

Multi-sensor fusion (camera, LiDAR, IMU, encoders)

Robot control and integration

Proven track record of deploying algorithms in real-world systems.

Strong programming skills in Python, with experience in frameworks like ROS,PyTorch or Tensorflow.

Deep knowledge in the areas of robot locomotion, robot kinematics and robot dynamics.

Comfortable working with real-time systems, embedded platforms, or simulators such as Gazebo, Isaac Sim, MuJoCo, OpenAI Gym or Unreal Engine.

Familiar with MLOps and software best practices: CI/CD, containerization (Docker), orchestration (Kubernetes), etc.

Excellent communicator and collaborator — capable of leading multi-disciplinary teams and influencing stakeholders across hardware, software, and business domains.

Bonus Experience (Nice to Have)

Familiarity with industrial domains: factory automation, AMRs, predictive maintenance, etc.

Prior contributions to open-source projects

Understanding of sensor design, signal processing, or embedded AI hardware platforms.

Why Join ADI?

Join us in shaping the future of edge intelligence — where your work bridges the gap between sensing and understanding, and where you’ll help machines not just gather data, but act meaningfully in the world.

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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.

Job Req Type: Experienced

Required Travel: Yes, 10% of the time

Shift Type: 1st Shift/Days