# OpenAI Residency 2026

> The OpenAI Residency is a six-month research program in San Francisco that embeds talented individuals within OpenAI’s research teams to work on frontier AI problems with mentorship and real project contributions.

- **Organizer:** OpenAI
- **Category:** research
- **Region:** North America
- **Country:** United States
- **Votes:** 16
- **Apply:** [https://openai.com/careers/residency-2026-san-francisco/](https://openai.com/careers/residency-2026-san-francisco/)
- **Page:** https://fellows.best/opportunity/openai-residency-2026
- **Markdown:** https://fellows.best/opportunity/openai-residency-2026.md

**Deadline:** Closed (2026-02-15)

**Funding:** 18300 USD (stipend)

**Tags:** ai-research, residency, mentorship, paid-research, san-francisco

## About

OpenAI’s Residency program is designed to identify and develop exceptional talent for frontier AI research. Residents join as full-time employees for six months, working directly with research teams on ambitious projects, receiving mentorship, and gaining practical research experience. The program values originality, rapid learning, and strong technical foundations, and some residents may be considered for full-time roles upon successful completion. Residency participants work in San Francisco with a hybrid, in-person collaboration schedule and receive competitive compensation and relocation support where applicable.

## What you'll get

- Six-month immersive research residency embedded with OpenAI’s research teams
- Direct mentorship from experienced AI researchers and engineers
- Full-time salary (competitive compensation, e.g., ~$18,300/month)
- Hands-on work on ambitious, cutting-edge AI projects
- Opportunity to contribute to active research directions and experiments
- Potential consideration for full-time roles at the end of the residency
- Relocation assistance available for San Francisco participation

## Eligibility

Individuals with strong technical ability and a high learning trajectory in areas like software engineering, research, mathematics, physics, neuroscience, or related fields; candidates may be self-taught, independent builders, or non-traditional backgrounds with demonstrated problem-solving and research potential.

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