ML Infrastructure Engineer: Build Scalable GPU Clusters

Cursor; California (MO); On-site; USD 140,000 - 185,000; Full time

Job summary

Cursor is seeking an experienced ML infrastructure engineer to help build and optimize high-performance GPU infrastructure that supports large-scale RL workloads. You will work closely with ML researchers and engineers to enhance training frameworks, reliability, and developer experience.

You will contribute to automation, monitoring, and scalable cluster management, leveraging Python, Typescript, Rust, and Golang across Linux-based environments and Kubernetes.

Qualifications

• Strong background in systems and infrastructure-focused software engineering.
• Proficient in Python, Typescript, Rust and Golang.
• Experience with distributed storage and networking.
• Experience with Kubernetes and Linux-based deployments.

Responsibilities

• Collaborate with ML researchers and engineers to improve throughput and reliability of training.
• Plan and build cutting-edge GPU infrastructure with OEMs and cloud providers.
• Improve density and scalability of compute environments for large RL workloads.
• Create software to automate building, monitoring, and running GPU clusters.
• Develop workload scheduling and data movement systems for Cursor’s training footprint.

Skills

Systems engineering

Python

Typescript

Rust

Golang

Distributed systems

Tools

Kubernetes

Linux

Job description

Cursor is seeking an experienced ML infrastructure engineer to help build and optimize high-performance GPU infrastructure that supports large-scale RL workloads. You will work closely with ML researchers and engineers to enhance training frameworks, reliability, and developer experience.

You will contribute to automation, monitoring, and scalable cluster management, leveraging Python, Typescript, Rust, and Golang across Linux-based environments and Kubernetes.