Compute Optimization Researcher/Engineer

About the Team OpenAI’s infrastructure organization builds and operates the systems that power frontier AI workloads at global scale. As our compute footprint expands across first-party data centers, cloud providers, and strategic partners, efficient capacity planning and resource allocation become critical to delivering reliable and cost-effective compute. The Compute Optimization team sits at the intersection of engineering, operations, finance, and infrastructure strategy.

We develop the models, decision systems, and planning frameworks that optimize how compute resources are deployed, scheduled, and scaled across a rapidly growing global environment. About the Role We are seeking Compute Optimization Researcher/Engineer to build the systems that maximize the value of OpenAI’s global compute capacity. In this role, you will work on high-impact optimization problems spanning capacity allocation, demand forecasting, cluster planning, workload placement, and infrastructure utilization.

You will combine mathematical modeling, software systems, and cross-functional execution to improve how compute is planned and consumed across GPU clusters, networking, storage, and data center environments. This role is ideal for candidates with backgrounds in operations research, optimization, applied math, infrastructure systems, or large-scale capacity planning. This role is based in San Francisco, CA.

We use a hybrid work model of 3 days in the office per week and offer relocation assistance. In this role, you will - Build optimization models for compute allocation, workload scheduling, and cluster utilization. - Develop planning systems that balance supply, demand, cost, latency, and reliability constraints.

• Create forecasting frameworks for GPU demand, infrastructure growth, and capacity needs. - Design decision tools for allocating compute across internal teams, products, and strategic priorities. - Partner with architecture, infrastructure engineering, finance, and operations teams to translate business needs into mathematical models.
• Integrate multiple operational data sources into planning systems and optimization workflows. - Improve utilization of GPUs, networking, power, cooling, and storage infrastructure. - Analyze tradeoffs across first-party data centers, cloud providers, and hybrid environments.
• Build dashboards, metrics, and operational tooling for capacity decision-making. - Lead ambiguous, cross-functional initiatives that improve infrastructure efficiency at scale. - Present recommendations clearly to technical leaders and executives.
• Continuously refine models based on changing workloads, supply constraints, and business priorities. You might thrive in this role if you - Doctorate degree in Computer Science, Engineering, Mathematics, Operations Research, Economics, or related field. - 5+ years of experience in optimization, planning, infrastructure analytics, or systems engineering.
• Strong experience with linear programming, mixed-integer optimization, convex optimization, simulation, or forecasting methods. - Proficiency in Python and data tooling (SQL, Pandas, Spark, etc.). - Experience translating real-world business constraints into scalable optimization systems.
• Strong analytical problem-solving skills with comfort operating in ambiguous environments. - Ability to influence cross-functional stakeholders without formal authority. - Excellent communication skills with both technical and non-technical audiences.

Preferred Qualifications - Experience with large-scale infrastructure, cloud capacity planning, or data center operations. - Familiarity with tools such as Gurobi, CPLEX, CVXPY, Pyomo, or similar solvers. - Experience optimizing GPU fleets, networking systems, or distributed compute environments.

• Background in supply-demand planning, logistics, marketplace optimization, or resource scheduling. - Experience working in fast-scaling technology environments. 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 https://cdn.openai.com/policies/eeo-policy-statement.pdf. 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.

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