Principal Robotics AI/ML Engineer

About the position 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. Requirements • 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. Nice-to-haves • 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.