Senior AI Research Scientist (Model-based RL)
Core
Designing and deploying model-based reinforcement learning agents and world models for industrial control systems to enable facilities to automatically learn and improve.
Role type
Senior AI Research Scientist (Model-based RL)
Builds
Intelligent control systems for industrial facilities (factories, power plants) that adapt to their environment.
Domain
Industrial automation, Model-based Reinforcement Learning, Control Theory
Deliverable
production ML models
Required skills
Model-based reinforcement learning, Planning algorithms (MPC, MPPI), World models / learned dynamics surrogates, Deep learning, Control Theory, Safe/constrained RL, Research design, Sim-to-real gap closure
Preferred skills
PhD in ML/Control, Hands-on experience with industrial dynamical systems, Python, PyTorch, Vectorized/differentiable simulators, Distributed compute (Ray, Kubernetes, GCP), Publications in RL/Control
Technologies
Python, PyTorch, scipy, Kubernetes, Docker, Ray, GCP
Responsibilities
Design and implement model-based RL agents and planning controllers; Develop learned dynamics and world models with training pipelines; Research safe RL and constrained control methods; Report and present research findings; Collaborate on ambitious research projects; Mentor Research Engineers; Define new research directions and own research area rollout
Seniority
Senior, hands-on IC with research leadership
