OpenAI

Data Scientist, Inference Capacity Optimization

San Francisco · Remote·$293K–325K

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About the Role

OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models.

We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience.

You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments.

Key Responsibilities

  • Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency.
  • Develop forecasting models for inference demand across products, regions, and model families.
  • Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities.
  • Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies.
  • Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs.
  • Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions.
  • Collaborate with Product, Research, Finance, and Infrastructu
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