Research Engineer, AI for Science

OpenAI for Science is building the next great scientific instrument: an AI-powered platform that accelerates scientific discovery. We aim to prove that OpenAI’s frontier models can do real science—and help researchers everywhere do more, faster.

About the Role

As a Research Engineer, you will build AI systems that enable previously impossible capabilities or achieve unprecedented levels of performance. You’ll work at the intersection of engineering and research, designing, implementing, and improving large-scale machine learning systems while contributing to the science behind the algorithms themselves.

We’re looking for people with strong engineering fundamentals who enjoy writing high-quality ML code, are comfortable working at massive scale, and are excited about OpenAI’s approach to research. As deep learning systems continue to scale, engineering excellence will play a critical role in driving the next major advances in AI.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design, implement, and improve large-scale distributed machine learning systems

• Write robust, high-quality machine learning code and contribute to performance-critical components

• Collaborate closely with researchers to translate ideas into scalable, production-ready systems

• Have strong programming skills and enjoy building reliable, high-performance systems

• Are comfortable working in large distributed systems and at significant computational scale

• Are excited about OpenAI’s research direction and motivated by the real-world impact of AI

• Nice to have:

  • Interest in using AI to accelerate scientific discovery, improve experimental design, or enable new forms of scientific insight

  • Experience building high-performance implementations of deep learning algorithms