9 months ago
Responsibilities
- Collaborate with ML researchers to improve training throughput and reliability.
- Plan and build GPU infrastructure with OEMs, cloud service providers, and other partners.
- Improve the density and scalability of compute environments for increasingly large reinforcement-learning workloads.
- Create software and systems to automate building, monitoring, and running GPU clusters.
- Build workload scheduling and data movement systems for Cursor’s training infrastructure.
Requirements
- Strong background in systems and infrastructure-focused software engineering, particularly with Python, TypeScript, Rust, and Golang.
- Experience with distributed storage and networking infrastructure on Linux systems across cloud and bare-metal environments.
- Exposure to large-scale systems, ideally across thousands of nodes with significant resource footprints.
- Production use of infrastructure-as-code and configuration management across hosts and Kubernetes.
- Experience with Nvidia GPUs, InfiniBand or RoCE, Blackwell or Hopper hardware, Ray, or Slurm is a nice-to-have.
Tech Stack
Categories
About Cursor
Cursor is an AI-powered code editor and coding assistant from Anysphere, built for professional software engineers and enterprise teams. It combines a VS Code–style editor with integrated AI chat, code generation, and repo-aware refactoring, and is sold via individual, team, and enterprise subscriptions. The company also targets sectors like healthcare and state and local education with field engineers who support evaluations and proofs of concept.