Research Engineer / Scientist – Reinforcement Learning (RL)

Percepta; New York (NY); On-site; USD 110,000 - 150,000; Full time

Job summary

A cutting-edge AI company in New York seeks a Research Engineer/Scientist specializing in Reinforcement Learning. In this role, you will tackle real-world challenges and develop RL methods to optimize operations across critical industries. Ideal candidates will hold an MS/PhD in Computer Science or related fields and have strong programming skills, particularly in Python. Join us if you're excited about leveraging AI for transformative impact in various sectors, including healthcare and finance.

Qualifications

• Have a track record of effective RL work.
• Strong programming skills, especially in Python.
• Experience with vLLM/SGLang and multi-node training.

Responsibilities

• Identify tractable real-world challenges for RL.
• Develop RL methods for planning and optimization.
• Conduct evaluations that drive significant value.

Skills

Reinforcement Learning

Python

Large scale distributed systems

Rigorous RL experimentation

Asynchronous training and inference

Education

MS/PhD in Computer Science, ML, or related field

Tools

Ray

Kubernetes

AWS EKS

Job description

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 Engineer/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.

Role and 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.

Indicators of a good fit

• 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.

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. If that excites you, let's chat, even if you don't meet all of the qualifications above.