Research Scientist – Reinforcement Learning (RL)

Percepta • Boston, MA

2d

About The Position

As a Research Scientist - Reinforcement Learning at Percepta, you will work at the intersection of RL research and real-world deployment. You will advance the frontier of capabilities through research on decision-making for critical industries. You will collaborate closely with our Embedded Product Managers (EPMs) and engineers to ensure that our solutions transform how companies operate.

Requirements

• MS/PhD in Computer Science, ML, or related field, or equivalent experience.
• A track record of effective RL work.
• Motivated by impact in critical industries including healthcare, supply chains, energy, and finance.
• Understand how to perform rigorous RL experimentation.
• Enjoy extreme ownership.
• Believe that AI can drive transformative change in critical industries.
• High performance, large scale distributed systems.
• Large scale LLM training or RL training.
• Possess strong programming skills, especially in Python.
• Implementing LLM post-training algorithms.
• Experience with vLLM/SGLang, Ray, Kubernetes (or AWS EKS).
• Experience with distributed checkpointing, multi-node, multi-gpu training, custom KV-caching.
• Experience with asynchronous training and inference, either with VeRL, ROLL, SkyRL, AReal, or with RL libraries like CleanRL.

Responsibilities

• Identifying which real-world challenges are tractable for RL-guided decision making.
• Develop RL methods to perform complex tasks in domains like planning, decision-making, or optimization.
• Develop and maintain the experimental infrastructure that powers our research, from simulation environments and data pipelines to training and evaluation frameworks.
• Conduct in-the-wild evaluations at scale that drive millions of dollars in value.
• Partner with our applied AI engineers to transition successful research ideas into robust features of our Mosaic platform.
• Communicate research outcomes to both technical and non-technical stakeholders, making sure everyone understands the “so what” of research and how to apply it.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior