Application Guide
How to Apply for Senior AI Research Scientist (Model-based RL)
at Phaidra
🏢 About Phaidra
Phaidra stands out for its mission-driven focus on using AI to drastically reduce industrial energy waste and environmental impact, while also offering a fully remote, collaborative culture. The company applies cutting-edge AI research directly to real-world industrial control systems, making a tangible difference in sustainability.
About This Role
As a Senior AI Research Scientist, you will lead the development of model-based RL agents that control industrial systems, directly impacting energy efficiency. Your work involves designing planning-based controllers, building world models, and ensuring safe deployment, bridging the gap between research and practical impact.
💡 A Day in the Life
A typical day might start with a stand-up with your research team to discuss progress on world model training, followed by coding a new planning algorithm in Python. After lunch, you might mentor a junior researcher on sim-to-real transfer, then analyze experimental results from a deployed controller on a real industrial plant, iterating on safety constraints.
🚀 Application Tools
🎯 Who Phaidra Is Looking For
- Deep expertise in model-based RL, including planning algorithms like MPC or MPPI, with a strong publication record in top venues (NeurIPS, ICML, CoRL).
- Hands-on experience closing the sim-to-real gap, e.g., deploying RL agents on physical systems or working with industrial simulators.
- Solid understanding of safe RL and constrained control, with practical experience implementing safety constraints.
- Proven ability to mentor junior researchers and translate complex research into deployable solutions.
📝 Tips for Applying to Phaidra
Highlight specific projects where you designed and deployed model-based RL agents on real hardware, not just simulations.
Emphasize any experience with industrial control systems (e.g., HVAC, data centers) or related domains like robotics.
Showcase your work on safety and constraints, e.g., papers on safe RL or constrained MDPs.
Tailor your CV to include metrics: energy savings, sample efficiency, or deployment success rates.
Mention familiarity with Phaidra's technology stack (e.g., Python, TensorFlow/PyTorch, ROS) and industrial protocols.
✉️ What to Emphasize in Your Cover Letter
['Your passion for using AI to tackle climate change and industrial efficiency.', "Specific examples of model-based RL projects you've led, especially those with real-world deployment.", "Your experience with safe RL and how you've ensured reliability in autonomous systems.", "Why Phaidra's mission and remote culture align with your career goals."]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Read Phaidra's blog posts and case studies on their AI control systems for industrial plants.
- → Review recent papers from Phaidra's research team (e.g., on model-based RL or safe control).
- → Understand the industrial domains Phaidra targets (e.g., data centers, steel plants) and their specific challenges.
- → Familiarize yourself with the company's values: remote-first, interdisciplinary collaboration, and environmental impact.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Overemphasizing model-free RL or deep learning without connecting to model-based control or planning.
- Lack of concrete examples of real-world deployment; avoid purely theoretical work.
- Ignoring safety and constraints; this role is critical for industrial applications where failures are costly.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!