Who We Are

Percepta’s mission is to transform critical institutions with applied AI. We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.

To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:

Forward-deployed expertise in engineering, product, and research

Mosaic, our in-house toolkit for rapidly deploying agentic workflows

Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more

Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives.

Percepta is a direct partnership with General Catalyst, a global transformation and investment company.

About the role

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.

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.

You may be a good fit if you

Have an MS/PhD in Computer Science, ML, or related field, or equivalent experience.

Have a track record of effective RL work.

Are 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.

The following list can be a sign that you might be a good technical fit:

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.

About Our Team

As an organization, Percepta is committed to inclusion and belonging, and our people are our greatest investment! We’re working against an incredibly ambitious mission. It won’t be easy, but it will likely be the most fulfilling work of your career.

In addition to competitive compensation, equity, 401(k) matching, comprehensive health and family benefits, and lunch every day, we offer a culture built on autonomy and trust. We strongly believe that the boldest solutions come from teams who dream bigger together, and that means bringing in people from every kind of background, experience, and path. We are an office-first team that values the impact of in-person collaboration, but we focus on outcomes over outputs—believing that we are each responsible for solving the "whole problem" to make our customers win.

If you don't check every box on this description but you care deeply about the problems we're tackling, seeking the truth, and wanting to own outcomes alongside a team that has your back, then we want to hear from you! We know self-doubt keeps great people from applying, so please don't count yourself out before we've had the chance to meet you. Tackling the hardest problems takes a range of perspectives in the room, and we believe that's how we build something truly game-changing.