Software Engineer, Productivity - Model Performance
OpenAIAbout the Team
We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale.
About the Role
We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence.
This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI.
In this role you will:
Improve development workflows for engineers working on model performance infrastructure
Design and improve CI/CD, release, validation, and testing pipelines
Build and maintain tools that improve reliability, iteration speed, and engineering confidence
Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows
Contribute to infrastructure efforts that support performance-critical training and inference systems
Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure
Work in a high-context, ambiguous environment where ownership and good judgment matter
You might thrive in this role if:
You are motivated by enabling the people around you and helping engineers do their best work
You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows
You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams
You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure
You have experience improving large-scale engineering workflows, especially around CI reliability, test infrastructure, and debugging velocity
You are self-directed and comfortable operating with ambiguity