The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement.
- Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management.
- Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling.
- Automate capacity management and incorporate platform-wide health monitors.
- Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards.
- Improve end-to-end feedback loops for continual model improvement.
Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API.
- Elevate and consolidate ChatGPT's harness, context management, and system prompt frameworks.
- Drive expansion and improvement of multi-tier model experiences.
- Support and scale self-serve experiment capabilities and automated guardrails.
- Lead model rollout automation, capacity management, and health monitoring.
- Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.).
- Proven experience leading engineering teams in complex, cross-functional environments.
- Demonstrated success shipping production systems at scale (ideally for AI or large backend services).
- Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling.
- Excellent communication and collaboration skills-experience interfacing directly with engineering, research, and product stakeholders.
- Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus.
- Tackle highly impactful technical challenges at the cutting edge of AI.
- Collaborate with world-class researchers, engineers, and product leaders.
If you're passionate about advancing AI reliability, safety, and user impact at a global scale, we encourage you to apply!
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