🛠 Tech Stack

💼 About This Role

You'll build optimization models and planning systems for OpenAI's global compute capacity. You'll maximize utilization across GPU clusters, networking, and data centers. This role combines mathematical modeling with cross-functional execution at scale.

🎯 What You'll Do

• Build optimization models for compute allocation and workload scheduling.
• Develop planning systems balancing supply, demand, cost, and reliability.
• Create forecasting frameworks for GPU demand and capacity needs.
• Design decision tools for allocating compute across internal teams.

📋 Requirements

• Doctorate degree in Computer Science, Engineering, or related field.
• 5+ years experience in optimization, planning, or infrastructure analytics.
• Strong experience with linear programming, mixed-integer optimization, or simulation.
• Proficiency in Python and data tooling (SQL, Pandas, Spark).

✨ Nice to Have

• Experience with large-scale infrastructure or cloud capacity planning.
• Familiarity with tools like Gurobi, CPLEX, CVXPY, or Pyomo.
• Background in GPU fleet optimization or distributed compute environments.

🎁 Benefits & Perks

• 💰 Competitive salary with equity
• 🏖️ Hybrid work model with 3 days in office
• 🚀 Relocation assistance available
• 🏥 Health insurance (implied by location/industry)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite Interviews· 3 hours