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Software Engineer, ML Platform
Summary by AIEngineer.careers
Software Engineer, ML Platform is a AI Platform Engineer role (full-time). with Cursor. in SAN FRANCISCO, US. Imported listing (source: zerogtalent.com). Apply on the employer's site (zerogtalent.com).
Imported listing (source: zerogtalent.com) · Apply on zerogtalent.com
SAN FRANCISCO · US
—
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from zerogtalent.com
Cursor is seeking a Software Engineer for its ML Platform team to build and maintain core infrastructure supporting ML research and product development. You will design distributed systems, data pipelines, and observability tools that enable researchers to train models efficiently on large GPU fleets. This role involves close collaboration with research teams to streamline experiment tracking, telemetry ingestion, and compute scheduling in a high-ownership, fast-paced environment.
Responsibilities
- Design, build, and operate core platform systems for ML researchers and product engineers
- Partner with research teams to develop durable infrastructure and improve developer experience
- Own reliability, performance, and scalability of distributed systems and data pipelines
- Ship iteratively in a flat, high-ownership environment while measuring impact
Requirements
- Strong background in systems and infrastructure software engineering
- Experience owning production distributed systems at scale (ingestion, pipelines, orchestration)
- Proficiency with Linux, cloud/bare metal environments, and modern orchestration (Kubernetes, Ray)
- Ability to collaborate closely with ML researchers and product engineers
- Thrives in high-ownership environments with short feedback loops
Cursor
San Francisco · US · 829+ employees
Cursor is an AI-native code editor and developer platform designed to improve developer productivity through integrated AI features. The platform offers capabilities like full codebase understanding, autonomous coding agents, and a proprietary Composer model to facilitate high-level software development.
