Job Description
📋 Description Design, implement, and evaluate model-based RL agents for industrial control. Develop learned dynamics and world models across different systems. Research safe RL, constrained control, scenario planning, Bayesian RL. Translate research into production solutions and rollout. Communicate findings via docs, presentations, and discussions. Collaborate with research teams, engineers, and external partners. 🎯 Requirements PhD in ML/controls/CS or related field, or equivalent experience. At least 2 years of post-PhD research experience. Deep knowledge in model-based RL, safe RL, planning, world models, or control theory. Experience building AI agents using simulators and sim-to-real transfer. Strong Python, PyTorch, and SciPy experience. Experience with scalable experimentation environments: Ray, Kubernetes, Docker, or GCP. 🎁 Benefits Fully remote with flexible time zones. Eligibility for meaningful equity participation. Health insurance (medical, dental, vision) varies by location. Unlimited PTO with a minimum of 20 days per year. Paid parental leave, depending on regional policies. Flexible stipends for workspace, wellbeing, and development.
