Software Engineer, ML Research

Cursor; California (MO); On-site; USD 100,000 - 140,000; Full time

Job summary

Cursor is building the future of coding and training frontier coding agents. We are a small, flat team focused on truth-seeking and creative solutions. You will work with researchers to make progress repeatable and iteration fast.

The Research Engineer role involves building training and inference infrastructure, writing data processing libraries, and shaping data pipelines from user data into effective training data.

Qualifications

• Strong background in infrastructure/distributed systems
• Ability to architect and ship end-to-end with high ownership
• Interest in learning more about ML and language models

Responsibilities

• Build the distributed training, inference, and RL infrastructure
• Write libraries to simplify large-scale data jobs for researchers
• Architect systems turning Cursor user data into effective training data

Skills

Distributed systems

Infrastructure

End-to-end ownership

ML concepts

Job description

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

Research Engineer

Cursor is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective.

About the role

We’re looking for Research Engineers to build the training, inference, and data systems behind our frontier coding models. You’ll work directly with researchers to make progress repeatable and iteration fast.

What you’ll do

• Build our distributed training, inference, and RL infrastructure

• Write libraries to simplify how researchers do large-scale data jobs

• Architect the systems that turn Cursor user data into effective training data

You may be a fit if

• You have a strong infrastructure/distributed systems background

• You are able to architect and ship end-to-end with high ownership

• You have strong intuitions about how language models work

• You’re excited to learn more about ML

#LI-DNI