CursorSan Francisco, CABuilds large-scale ML infrastructure including GPU clusters, training frameworks, and workload schedulers. Requires strong systems engineering in Python, Rust, Golang, with Kubernetes and distributed systems experience.
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.
Build and ship production AI agents on Cloudflare's edge platform using Workers, Durable Objects, and AI tools. Requires strong TypeScript/Rust experience, observability expertise, and hands-on LLM tooling for evals, safety, and multi-agent systems.
Characterize, analyze, and optimize performance of state-of-the-art AI models on Cerebras' wafer-scale hardware. Build performance models, optimize kernels and compilers, debug runtime behavior, and develop visualization tools to influence next-gen AI architecture.
Research Engineer on OpenAI's Privacy team designing and prototyping privacy-preserving ML algorithms like differential privacy and federated learning at scale. Requires hands-on PETs experience, fluency in PyTorch/JAX, and a track record implementing or publishing novel privacy work.
Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.
Build and scale the shared AI platform foundations at Notion, enabling fast and safe shipping of AI products. Requires experience with LLM/ML platforms, strong ownership, and comfort across backend, infrastructure, and product code.