Compute Optimization Researcher/Engineer

Compute Optimization Researcher/Engineer 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 are 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 a Compute Optimization Researcher/Engineer to build systems that maximize the value of OpenAI’s global compute capacity. Your work will span capacity allocation, demand forecasting, cluster planning, workload placement, and infrastructure utilization, combining 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. Location: San Francisco, CA (hybrid work model – 3 days in the office per week with relocation assistance). Responsibilities 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. Qualifications Doctorate degree in Computer Science, Engineering, Mathematics, Operations Research, Economics, or a 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. Compensation $293K – $455K + offers equity. Equal Employment Opportunity OpenAI is 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. 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 U.S.-based candidates. #J-18808-Ljbffr OpenAI