Phaidra

22 hours ago

Senior AI Research Scientist (Model-based RL)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Build and evaluate model-based reinforcement learning agents for industrial control systems, including planning-based controllers (MPC, MPPI) and deployable software prototypes. Develop learned dynamics and world models to generalize across systems, and research methods such as safe RL, constrained control, scenario planning, and Bayesian RL. Present results, lead/own research areas, mentor Research Engineers, and collaborate with external partners to translate research into production outcomes.

Location: United Kingdom, Sweden, Spain, Portugal, Netherlands

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 the software prototypes to deploy them on industrial control systems.
•Develop learned dynamics and world models (learned surrogates) with training pipelines such as pretraining, curriculum learning, active/adversarial learning, and fine-tuning.
•Research and implement safe RL and constrained control methods (e.g., scenario planning and Bayesian RL) to satisfy safety constraints during deployment.
•Report and present research findings and developments clearly and efficiently, verbally and in writing.
•Mentor Research Engineers, define new research directions, translate research into practical outcomes, and own development/rollout for a research area or large project.

Pay and Benefits

Salary: GBP 87,681 - 165,379 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionPaid LeaveRemote WorkHome OfficeWellness StipendLearning Budget

Key Requirements

•PhD in a technical field (or equivalent practical experience) with strong model-based reinforcement learning background and knowledge across planning algorithms, world models/learned dynamics, reinforcement learning/deep learning, control theory, and/or safe/constrained RL.
•2+ years of research experience in academia or industry after PhD graduation.
•Extensive research in model-based/model-free/safe 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.
•Share company values: collaboration, transparency, operational excellence, ownership, and empathy.

Experience:Reinforcement learningControl theoryIndustrial automation

Education:PhD / Doctorate

Skills:CollaborationTransparencyOperational excellenceOwnershipEmpathyCommunication

Languages:English

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

Website

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Phaidra

22 hours ago

Senior AI Research Scientist (Model-based RL)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 14 hours agoStatus: Live

Job Summary

Location: United Kingdom, Sweden, Spain, Portugal, Netherlands

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 the software prototypes to deploy them on industrial control systems.
•Develop learned dynamics and world models (learned surrogates) with training pipelines such as pretraining, curriculum learning, active/adversarial learning, and fine-tuning.
•Research and implement safe RL and constrained control methods (e.g., scenario planning and Bayesian RL) to satisfy safety constraints during deployment.
•Report and present research findings and developments clearly and efficiently, verbally and in writing.
•Mentor Research Engineers, define new research directions, translate research into practical outcomes, and own development/rollout for a research area or large project.

Pay and Benefits

Salary: GBP 87,681 - 165,379 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionPaid LeaveRemote WorkHome OfficeWellness StipendLearning Budget

Key Requirements

•PhD in a technical field (or equivalent practical experience) with strong model-based reinforcement learning background and knowledge across planning algorithms, world models/learned dynamics, reinforcement learning/deep learning, control theory, and/or safe/constrained RL.
•2+ years of research experience in academia or industry after PhD graduation.
•Extensive research in model-based/model-free/safe 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.
•Share company values: collaboration, transparency, operational excellence, ownership, and empathy.

Experience:Reinforcement learningControl theoryIndustrial automation

Education:PhD / Doctorate

Skills:CollaborationTransparencyOperational excellenceOwnershipEmpathyCommunication

Languages:English

Tech Stack:PythonPyTorchScipyKubernetesDockerRayGCP

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Phaidra

Industry: AI & Machine Learning

Website