Compute Optimization Engineer

New

Skills

Cluster utilization Convex optimization GPU demand forecasting Linear programming (LP) Mixed-integer linear programming (MILP) Optimization models Python SQL Supply and demand planning Workload scheduling

As a Compute Optimization Researcher/Engineer, you will play a crucial role in enhancing our compute allocation processes, workload scheduling, and cluster utilization. You will develop advanced planning systems that effectively balance supply, demand, cost, latency, and reliability, while also creating forecasting frameworks to predict GPU demand, infrastructure growth, and capacity needs.

Key Responsibilities
  • Build optimization models for compute allocation and workload scheduling.
  • Develop planning systems to balance supply, demand, cost, latency, and reliability.
  • Create forecasting frameworks for GPU demand and infrastructure capacity needs.
  • Design decision tools for compute allocation across teams and priorities.
  • Collaborate with architecture, infra engineering, finance, and operations to translate needs into models.
  • Integrate multiple operational data sources into planning systems and optimization workflows.
Required Skills & Qualifications
  • Doctorate degree in CS, Engineering, Mathematics, Operations Research, Economics, or related field.
  • 5+ years of experience in optimization, planning, analytics, or systems engineering.
  • Strong experience with LP, MILP, convex optimization, simulation, or forecasting.
  • Proficiency in Python and data tooling (SQL, Pandas, Spark).
  • Experience translating real-world constraints into scalable optimization systems.
  • Strong analytical problem-solving skills and ability to influence cross-functional stakeholders.

No forms. Your profile is generated instantly.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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