Senior AI Research Scientist, Model-based RL
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Job Description
Senior AI Research Scientist developing model-based reinforcement learning for Phaidra’s AI-powered industrial automation systems. Designing safe agents, world models, and planning controllers for real-world deployment.
Responsibilities:
- Design, implement, and evaluate model-based reinforcement learning agents, including MPC and MPPI planning-based controllers
- Develop software prototypes for deployment on real industrial control systems
- Develop learned dynamics and world models that generalize across systems
- Build training pipelines involving pretraining, curriculum learning, active/adversarial learning, and fine-tuning
- Research and implement safe RL, constrained control, scenario planning, and Bayesian RL methods
- Report and present research findings and developments internally and externally, verbally and in writing
- Participate in and organize collaborative research projects
- Work with external collaborators and partners to translate research into production outcomes
- Mentor and guide Research Engineers applying research to industrial domains
- Define new research directions, translate research into practical outcomes, and own development and rollout of a research area or large project
Requirements:
- PhD in a technical field or equivalent practical experience
- Strong background in model-based reinforcement learning
- Knowledge of planning algorithms, world models / learned dynamics surrogates, reinforcement learning and deep learning, control theory, or safe / constrained RL
- Either 2+ years of research experience after PhD graduation or 5+ years of research experience after Master’s graduation
- Extensive research in Model-Based, Model-Free, and Safe RL and Control Theory, with particular depth in model-based methods
- Hands-on experience building and evaluating agents against simulators and closing the sim-to-real gap
- Alignment with Phaidra's values: Agency, Velocity, Craft, and Truth
- Strong Python and PyTorch skills, including vectorized/differentiable simulators and distributed compute
- Proven track record of publications in RL, control, or a related area
- Legally authorized to work in the United Kingdom; no employment sponsorship available
- Candidates advancing beyond initial screening must sign an NDA
Benefits:
- 100% remote work
- Competitive compensation and meaningful equity
- Outsized responsibilities and professional development
- Functional, customer immersion, and development training
- Medical, dental, and vision insurance (exact benefits vary by region)
- Unlimited paid time off, with a required minimum of 20 days per year
- Paid parental leave (exact benefits vary by region)
- Flexible stipends for workspace, well-being, and continued professional development
- Company MacBook
- Virtual team-building activities and social events
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