Software Engineer, ML Infrastructure

Stack

Responsibilities

• ▹Collaborate with ML researchers to improve training throughput and reliability
• ▹Work with OEMs and cloud service providers 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

Requirements

• ▹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
• ▹Exposure to large-scale systems and their unique challenges, ideally across thousands of nodes with significant resource footprints
• ▹Production use of infrastructure-as-code and configuration management, across hosts and Kubernetes

Nice to have

• ▹Operational exposure to Nvidia GPUs with Infiniband or RoCE, particularly with Blackwell and Hopper-class hardware
• ▹Exposure to Ray, Slurm, or other common compute and runtime schedulers

Soft skills

About the company

Cursor, built by Anysphere, is on a mission to automate coding by building the best tool for professional programmers. The team is flat, small, and talent-dense, valuing truth-seeking, passion, and creativity.