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OpenAI's Product & Platform teams deliver the company's most impactful offerings—ChatGPT, the API platform, and enterprise capabilities—to a global customer base. The ChatGPT Multimodal team works across voice, image generation, and other multimodal experiences to turn frontier research capabilities into reliable products.
You will lead programs that help ChatGPT multimodal products learn from real-world usage and improve quickly. This role spans production-signal mining, evaluation and data pipelines, research-to-production parity, multimodal capacity planning, and complex cross-functional dependencies for voice and image-generation launches.
Key responsibilities include:
- Building systems to mine production conversations and product signals to identify representative multimodal workflows, user needs, and failure modes
- Establishing and maintaining evaluations for high-priority multimodal behaviors with clear coverage, quality standards, and ownership
- Packaging production signals into decision-ready data and evaluations for research teams to improve model behavior
- Measuring whether model, prompt, configuration, and product changes produce meaningful improvements in evaluations and user outcomes
- Closing gaps between research and production environments (system prompts, sampling behavior, multimodal configurations, inference differences)
- Creating repeatable processes for reproducing product failures with research partners and validating fixes
- Leading multimodal capacity planning by forecasting demand, translating to GPU and serving needs, and managing tradeoffs for voice and image-generation workloads
- Improving tooling and operating processes for planning, launching, and operating multimodal capabilities
- Coordinating targeted multilingual data collection across research, Human Data, and external vendors
- Driving cross-functional programs including multimodal actor recruitment and voice-related product partnerships
- Creating clear operating cadences, decision rights, metrics, risk management, and executive communication across complex programs
You will work closely with product engineering, research, Human Data, inference and capacity teams, safety partners, and external vendors. Success requires technical depth, strong systems thinking, comfort with ambiguity, and the ability to turn fragmented or manual work into durable mechanisms that teams adopt.
This is a hybrid role based in San Francisco, CA, requiring 3 days in the office per week. Relocation assistance is offered to new employees.
REQUIREMENTS:
- Led technically complex programs across machine learning, multimodal products, model evaluation, data pipelines, inference, capacity, or large-scale product infrastructure
- Ability to move fluently between user-facing product behavior and underlying model, evaluation, configuration, serving, and capacity systems
- Experience building mechanisms that convert production signals into prioritized evaluations, data, engineering work, and measurable product improvements
- Can reason credibly about GPU demand, serving constraints, latency, reliability, quality, and launch tradeoffs
- Experience closing research-to-production gaps and driving structured debugging and validation across teams with different environments and incentives
- Demonstrated ability to turn manual or fragmented workflows into scalable tooling, clear ownership, and durable operating practices
- Ability to lead effectively across research, engineering, product, operations, Human Data, and external partners without direct authority
- Strong communication skills; ability to make ambiguity tractable and use metrics and evidence to drive decisions
- Thrive in ambiguous, scaling environments and bring order to complex cross-functional work without losing pace
- Alignment with OpenAI's mission and commitment to expanding responsible access to advanced AI systems
