Software Engineer, ML Infrastructure

The ML Infrastructure team builds large-scale compute, storage, and software infrastructure to support Cursor’s work building the world’s best agentic coding model. We’re looking for strong engineers who are interested in building high-performance infrastructure and the software to support it. This role works closely with ML researchers and engineers to enable their work through improvements to our training framework, systems reliability/performance, and developer experience.

Collaborate with ML researchers to improve the throughput and reliability of training

Work with OEMs, cloud service providers, and others to plan and build cutting-edge GPU infrastructure

Improve the density and scalability of compute environments to enable increasingly large RL workloads

Create software and systems to automate building, monitoring, and running GPU clusters

Build workload scheduling and data movement systems to support Cursor’s growing training footprint

A strong background in systems and infrastructure-focused software engineering, particularly in Python, Typescript, Rust, and Golang

Experience with distributed storage and networking infrastructure, particularly on Linux systems across cloud and bare metal environments