5-7 years of experience in developer productivity, CI/CD, or infrastructure roles
Strong Python programming skills
Familiarity with CI reliability and testing systems
Ability to work collaboratively with technical teams
Experience with large-scale engineering workflows
Desire to learn about model performance and related domains
Familiarity with the PyTorch ecosystem is a strong advantage
Responsibilities
Enhance development workflows for engineers on model performance infrastructure
Design and optimize CI/CD, release, and testing pipelines
Develop and maintain reliable engineering tools
Collaborate with engineers to identify and eliminate workflow friction
Support infrastructure for performance-critical training and inference systems
Enhance developer experience in Python-focused environments
Operate effectively in a high-context and ambiguous environment
Benefits
Opportunity to work on cutting-edge AI technologies
Collaborative and innovative work environment
Potential involvement in significant projects like Triton
Focus on professional development and learning
Flexible work arrangements
Full Job Description
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
You do not need direct inference or model performance experience, but you are excited to learn the domain and make the team meaningfully more effective
Experience in the PyTorch ecosystem is highly relevant
Experience with C++ or Rust is a nice-to-have, but not required
When you see repeated friction - slow tests, flaky CI, brittle release processes, painful debugging, unclear validation - your instinct is to fix the underlying system
You are pragmatic and know how to balance high standards with forward progress
About OpenAI
OpenAI is an artificial intelligence research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company was founded in 2015 by a group of technology leaders, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and John Schulman. OpenAI's mission is to develop and promote friendly AI for the betterment of humanity. The company has developed a number of cutting-edge AI technologies, including GPT-3, a language processing system that can generate human-like text. OpenAI has received funding from a number of high-profile investors, including LinkedIn co-founder Reid Hoffman and venture capitalist Peter Thiel.
