Jobs / United Kingdom / Phaidra, LTD

Phaidra, LTD

Senior AI Research Scientist (Model-based RL)

Remote - United Kingdom · Remote · UK only Posted 2 months ago

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Based on the listing's location: Remote - United Kingdom.

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThis employer holds a UK sponsor licence (Skilled Worker, A rating).
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • Can’t check pay against the visa rulesNo salary stated. UK Skilled Worker visa needs at least £41,700 a year (new-entrant (under 26, recent Student/Graduate visa) or STEM PhD: £33,400).
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
This employer holds a UK sponsor licence (Skilled Worker, A rating). Source: Register of licensed sponsors (UK Home Office).
Can’t check pay against the visa rules
No salary stated. UK Skilled Worker visa needs at least £41,700 a year (new-entrant (under 26, recent Student/Graduate visa) or STEM PhD: £33,400). Source: https://www.gov.uk/skilled-worker-visa/when-you-can-be-paid-less, rules effective 2025-07-22.

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About the role

About Phaidra Phaidra is building the future of industrial automation. The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades. Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time. Specifically: • We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data into high-value actions and decisions. • We focus on industrial applications, which tend to be well-sensorized with measurable KPIs — perfect for reinforcement learning. • We enable domain experts (our users) to configure the AI control systems (i.e. agents) without writing code. They define what they want their AI agents to do, and we do it for them. Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with DeepMind's AlphaGo , to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact. Phaidra’s ability to achieve its mission is determined by our ability to work together — as defined by our core values: Agency, Velocity , Craft , and Truth . We seek individuals who embody these values, as they are instrumental in ensuring our team consistently delivers excellence and fosters an engaging and supportive culture Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR . Our team is currently located throughout the USA, Canada, UK, Sweden, Spain, Portugal, the Netherlands, Singapore, Australia, and India. Who You Are Research Scientists at Phaidra lead our efforts in developing novel algorithmic architecture towards the end goal of bringing intelligent control systems to industrial sector. Having pioneered research in the world's leading academic and industrial labs as PhDs, post-docs or professors, Research Scientists join Phaidra to work collaboratively within and across research fields. Drawing on expertise from a variety of disciplines including model-based reinforcement learning, planning and optimal control, deep learning, world models, and safe reinforcement learning, our Research Scientists are at the forefront of groundbreaking research and applying it to real-world industrial control systems. Responsibilities • Design, implement, and evaluate model-based reinforcement learning agents — including planning-based controllers (MPC, MPPI) — and the software prototypes needed to deploy them on real industrial control systems. • Develop learned dynamics and world models (learned surrogates) that generalize across systems, including the training pipelines — pretraining, curriculum learning, active/adversarial learning, and fine-tuning — needed to make them reliable for planning and control. • Research and implement methods for e.g. safe RL, constrained control, scenario planning and Bayesian RL, to develop agents that satisfy safety constraints during deployment. • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing. • Participate in and organize ambitious collaborative research projects, and work with external collaborators and partners to translate research into production outcomes. • Mentor

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