Senior AI Research Scientist (Model-based RL)

Phaidra
United Kingdom
Workplace: RemoteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Agency","Velocity","Craft","Truth","Collaboration","Mentoring","Research communication","Independent ownership"]

Build and evaluate model-based reinforcement learning agents for industrial control, including planning-based controllers such as MPC and MPPI. Develop learned dynamics and world models to generalize across systems, with training pipelines for reliable planning and control. Research safe and constrained RL methods to satisfy deployment safety constraints, and present findings to internal and external audiences. Mentor research engineers and independently define new research directions, translating work into practical production outcomes.

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Phaidra
Phaidra
1 day ago

Senior AI Research Scientist (Model-based RL)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 18 hours agoStatus: Live

Job Summary

Build and evaluate model-based reinforcement learning agents for industrial control, including planning-based controllers such as MPC and MPPI. Develop learned dynamics and world models to generalize across systems, with training pipelines for reliable planning and control. Research safe and constrained RL methods to satisfy deployment safety constraints, and present findings to internal and external audiences. Mentor research engineers and independently define new research directions, translating work into practical production outcomes.
Location: United Kingdom
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, implement, and evaluate model-based reinforcement learning agents, including planning-based controllers (MPC, MPPI) and software prototypes for industrial deployment.
  • •Develop learned dynamics and world models that generalize across systems, including reliable training pipelines (pretraining, curriculum learning, active/adversarial learning, fine-tuning).
  • •Research and implement methods such as safe RL, constrained control, scenario planning, and Bayesian RL to satisfy safety constraints during deployment.
  • •Report and present research findings clearly and efficiently, verbally and in writing, to internal and external audiences.
  • •Mentor and guide Research Engineers, independently define new research directions, and own development and rollout for an entire research area or large project.

Pay and Benefits

Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionPaid LeaveParental LeaveMacbook

Key Requirements

  • •PhD in a technical field (or equivalent practical experience) with strong model-based reinforcement learning knowledge, including planning algorithms, world models/learned dynamics, control theory, and safe/constrained RL.
  • •2+ years of research experience after PhD graduation, or 5+ years after Master’s graduation.
  • •Extensive research in model-based and related RL and control theory, with particular depth in model-based methods.
  • •Hands-on experience building and evaluating agents against simulators (e.g., differentiable simulators or world models) and closing the sim-to-real gap.
  • •Strong Python and PyTorch skills, including vectorized/differentiable simulators and scaling experiments on distributed compute (e.g., Ray, Kubernetes, GCP).
Experience:Industrial automationReinforcement learningModel-based RLControl theorySim-to-real
Education:PhD / Doctorate
Skills:AgencyVelocityCraftTruthCollaborationMentoringResearch communicationIndependent ownership
Tech Stack:PythonPyTorchScipyKubernetesDockerRayGCP

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Phaidra
Develops AI-driven solutions and tooling to help organizations build, deploy, and manage conversational agents and intelligent assistants, combining large language models with data connectors and orchestration for enterprise use cases.
Industry: AI & Machine Learning
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