At a glance
Build forecasting, statistical, and machine learning models to optimize inference capacity across OpenAI’s global GPU fleet, guiding infrastructure investments, scheduling strategies, and operational efficiency.
Summarized by AI from the original posting
What you'll do
- Build statistical and machine learning models to improve GPU utilization, latency, throughput, and fleet efficiency
- Develop forecasting models for inference demand across products, regions, and model families
- Analyze production workloads to identify latency bottlenecks and capacity constraints
- 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 for capacity decisions
- Collaborate with Product, Research, Finance, and Infrastructure teams on compute planning
- Communicate technical findings to engineering teams and executive leadership
Requirements
- 015+ years of experience working in infrastructure data science
- 02Strong expertise in Python and SQL
- 03Experience building forecasting, optimization, or predictive models
- 04Strong understanding of experimentation, statistical inference, and causal analysis
- 05Experience communicating analytical insights to executive stakeholders
Skills
Full description
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
Datacenter design and buildout
Queueing theory
Time-series forecasting
Operations research
Supply-demand modeling
Reinforcement learning for resource allocation
Cost optimization
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Compensation: $293K - $325K