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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 and guide Research Engineers to apply research findings and developments to industrial domains.
Independently defines new research directions Translates research into practical outcomes Owns the development and rollout for an entire research area or large project
Key Qualifications
PhD in a technical field or equivalent practical experience, with a strong background in model-based reinforcement learning and demonstrated knowledge in one or more of the following:
Planning algorithms
World models / learned dynamics surrogates
Reinforcement Learning and Deep Learning
Control Theory
Safe / constrained RL
Either:
2+ years of research experience in academia or industry after PhD graduation.
5+ years of research experience in academia or industry after Master’s graduation.
Extensive research in the fields of {ModelBased, ModelFree, 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.
Alignment with Phaidra's values: Agency, Velocity, Craft, & Truth.
Preferred Skills & Experience
PhD in machine learning, control, or a closely related field.
Deep, hands-on experience with model-based RL and planning agents applied to real-world dynamical or industrial systems.
Strong Python and PyTorch skills, including vectorized/differentiable simulators and scaling experiments on distributed compute (e.g. Ray, Kubernetes, GCP).
A proven track record of publications in RL, control, or a related area.
A real passion for AI and applying it to industrial systems to improve resource efficiency.
Our Stack Python PyTorch, scipy Kubernetes, Docker, Ray GCP Onboarding In your first 30 days...
You will be immersed in an onboarding program that introduces you to Phaidra and our product.
You will spend time in the research team and get introduced to the different tracks of research that we perform.
You will learn how other teams operate, interact, and approach problems.
You will read various parts of our handbook and familiarize yourself with the documentation culture at Phaidra.
You will set up your development environment and get introduced to various parts of our code base.
By your first 60 days...
You will have a solid understanding of what Phaidra does and how we do it.
You will have met with team members across Phaidra and started building relationships that will help you be successful at your job.
You will have a good understanding of our research tracks, which allowed you to form a plan for your first project, or maybe, you have already started one.
By your first 90 days...
You will have been fully integrated in the team and with team members across the company.
You will have started to contribute to knowledge sharing throughout Phaidra.
Your project is in full swing and you might have some early results already.
General Interview Process
All of our interviews are held via Google Meet, and an active camera connection is required.
Meeting with People Operations team member (30 minutes)
Meeting with Hiring Manager (30 minutes)
Technical Conversation with Research team member (60 minutes)
Technical Conversation with Hiring Manager (60 minutes)
Culture fit interview with Phaidra’s co-founders (30 minutes)
In addition to base salary, this position is eligible for equity. Final salary will be determined based on several factors, including a candidate’s qualifications, skills, competencies, experience, expertise, education and location. In some cases, final compensation may fall outside the posted range. Salary ranges are regularly reviewed and may be adjusted in response to market trends.
Benefits & Perks
Fast-paced, team-oriented environment where your work directly shapes the company’s direction.
We are a 100% remote company.
Competitive compensation & meaningful equity.
Outsized responsibilities & professional development.
Training is foundational; 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 to support your workspace, well-being, and continued professional development.
Company MacBook.
Please note: Not all of Phaidra’s benefits and perks listed above apply to temporary employees such as interns.
On being Remote
We take a thoughtful and intentional approach to remote collaboration. Inspired by pioneers like GitLab, we embrace proven best practices to foster an exceptional remote work environment. Our culture is documentation-first, and we prioritize asynchronous communication to support focus and flexibility across time zones. While we value independence, we stay closely connected through tools like Slack and video conferencing. Weekly all-hands meetings help us align and build strong relationships, and we regularly host virtual team-building activities and social events to maintain a sense of camaraderie.
Equal Opportunity Employment
Phaidra is an Equal Opportunity Employer; employment with Phaidra is governed on the basis of merit, competence, and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status. We welcome diversity and strive to maintain an inclusive environment for all employees. If you need assistance with completing the application process, please contact us at .
E-Verify Notice
Phaidra participates in E-Verify, an employment authorization database provided through the U.S. Department of Homeland Security (DHS) and Social Security Administration (SSA). As required by law, we will provide the SSA and, if necessary, the DHS, with information from each new employee’s Form I-9 to confirm work authorization for those residing in the United States.
Additional information about E-Verify can be found here.
To be considered for any position at Phaidra, you must submit an online application. This role will remain open until it is filled.
Phaidra only hires individuals who are legally authorized to work in the specified location(s) above. We do not provide employment sponsorship. Candidates requiring visa sponsorship, either now or in the future, are not eligible for hire.
Candidates who advance beyond the initial screening stage will be required to sign a Non-Disclosure Agreement (NDA) in order to continue through the interview process.
All employment offers are contingent upon successful completion of employment authorization verification and applicable background checks, in accordance with local laws and company policies.