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Job Description
📋 Description
- Design, implement, and evaluate model-based RL agents for industrial control.
- Develop learned dynamics and world models for planning and control.
- Explore safe RL, constrained control, and scenario planning techniques.
- Translate research into production results for real systems.
- Collaborate with external partners and mentor engineers.
🎯 Requirements
- PhD or equivalent experience with strong model-based RL background.
- 2+ years post-PhD or 5+ years post-Master’s in research.
- Deep RL, control theory, and knowledge of world models.
- Hands-on with simulators and sim-to-real work.
- Strong Python and PyTorch skills; experience with distributed compute.
🎁 Benefits
- Remote-first company with global teams.
- Competitive compensation and equity.
- Health, dental, and vision insurance; flexible stipends.
- Unlimited PTO and parental leave varies by region.
- MacBook provided; learning and growth opportunities.
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