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OpenAI

Data Scientist, Inference Capacity Optimization

Hybrid

Part remote, part office, you need to live within commuting distance of a named location.

Hybrid · San Francisco

Employer listed it 8 days ago · Added 5 days ago

First listed 8 days ago and still open.

Salary

$293,000 to $325,000

Location

Hybrid · San Francisco

Timezone

Not stated

Contract

Full-time

Experience

Mid

Category

Data

Published by the employer

Remote flexibility

Hybrid

This role is only partly remote, the employer expects time in the office around San Francisco, Hybrid, so you need to live within commuting distance.

What the employer says

  • Source listing states candidate location: "San Francisco, Hybrid"
  • Listing mentions "Hybrid"

What Nomaders makes of it

  • Not suitable if you plan to move between countries

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

About the role

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 Infrastructure teams to align compute planning with business growth and model roadmaps.

Communicate technical findings clearly to both engineering teams and executive leadership.

Qualifications

MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience).

5+ years of experience working in the infrastructure data science space.

Strong expertise in Python and SQL.

Experience building forecasting, optimization, or predictive models.

Strong understanding of experimentation, statistical inference, and causal analysis.

Experience communicating analytical insights to executive stakeholders.

Preferred Skills

Capacity planning

Distributed systems

AI infrastructure

Requirements

  • ·MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience).
  • ·5+ years of experience working in the infrastructure data science space.
  • ·Strong expertise in Python and SQL.
  • ·Experience building forecasting, optimization, or predictive models.
  • ·Strong understanding of experimentation, statistical inference, and causal analysis.

Benefits

No benefits package published with this listing. Ask about it at first interview.

How to apply

  1. 1Check the flexibility label above, hybrid, matches where you plan to live and work.
  2. 2Tailor your CV to the role at OpenAI, mentioning your remote working experience.
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 5d ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

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