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Phaidra is building AI-powered control systems for industrial automation. The company uses reinforcement learning to enable factories, power plants, and other industrial facilities to automatically learn and improve over time, moving away from hard-coded static controls that have remained unchanged for decades.
As a Senior AI Research Scientist specializing in model-based reinforcement learning, you will lead research efforts to develop novel algorithmic architectures for intelligent industrial control systems. You'll design, implement, and evaluate model-based RL agents including planning-based controllers (MPC, MPPI) and deploy them on real industrial systems.
Key responsibilities include:
- Developing learned dynamics and world models that generalize across systems, including training pipelines (pretraining, curriculum learning, active/adversarial learning, fine-tuning)
- Researching and implementing safe RL, constrained control, scenario planning, and Bayesian RL methods to ensure agents satisfy safety constraints during deployment
- Independently defining new research directions and owning development of entire research areas or large projects
- Translating research into practical production outcomes
- Mentoring Research Engineers to apply findings to industrial domains
- Presenting research findings clearly both internally and externally
- Collaborating with external partners to move research into production
You should have a PhD in a technical field (or equivalent) with strong background in model-based reinforcement learning and demonstrated expertise in planning algorithms, world models, deep learning, control theory, or safe/constrained RL. The role requires either 2+ years of research experience in academia or industry, with a track record of publishing or shipping production systems.
Phaidra is 100% remote with no physical office, hiring internationally across USA, Canada, UK, Sweden, Spain, Portugal, Netherlands, Singapore, Australia, and India. The team values Agency, Velocity, Craft, and Truth.
