Job Description
📋 Description Design, implement, and evaluate model-based RL agents (MPC/MPPI) for industrial control. Develop learned dynamics/world models generalizing across systems. Research safe RL, constrained control, scenario planning, Bayesian RL for reliability. Translate research into production-ready solutions and lead large-scale rollouts. Communicate findings via docs, presentations, and discussions. Collaborate with researchers, engineers, and partners to apply AI to industrial applications. 🎯 Requirements PhD in ML, control systems, CS, or related field; strong model-based RL expertise. At least 2 years of post-PhD research experience. Deep knowledge of model-based RL, model-free RL, safe RL, planning, world models. Experience building/evaluating AI agents with simulators and sim-to-real transfer. Strong Python programming with PyTorch and SciPy. Experience with scalable experimentation infra (Ray, Kubernetes, Docker, GCP) and strong publications. 🎁 Benefits Eligibility for meaningful equity participation. Fully remote with cross-time-zone flexibility. Medical, dental, and vision insurance (location dependent). Unlimited PTO with min 20 days/year. Paid parental leave, depending on regional policies. Flexible stipends for workspace, wellbeing, and dev; company MacBook.
