Product Manager, Compute Platform

Responsibilities

• Partner with Infrastructure to build systems that determine how jobs are scheduled, prioritized, and allocated across GPU and accelerator clusters
• Define the semantic layer for job scheduling: abstractions, priority tiers, resource classes, and preemption policies
• Partner with engineering leads to design scheduling capabilities that maximize cluster utilization while honoring resource guarantees
• Drive product strategy and roadmap for compute capacity management, including quota systems, fairness policies, bin-packing optimizations, and gang-scheduling
• Own the trade-off framework between utilization efficiency, job latency, cost, and reliability
• Collaborate with Capacity Strategy & Operations on capacity planning models, demand forecasting, and cost-to-serve analytics
• Build observability tools and dashboards for real-time visibility into cluster health, queue depth, scheduling efficiency, and resource waste

Requirements

• 7+ years of product management experience with deep exposure to compute infrastructure, distributed systems, or scheduling/orchestration platforms
• Experience taking technical infrastructure products from infancy to scale
• Track record of building platform products that balance needs of multiple users and stakeholders
• Ability to internalize complex technical systems and translate into product vision
• Fluent across functions: credible discussing scheduling algorithms with engineers, capacity economics with finance, and infrastructure strategy with leadership
• Strong instinct for connecting technical decisions to business outcomes

Nice-to-Haves

• Built or scaled job scheduling, resource orchestration, or workload management systems (Kubernetes, Slurm, Borg, YARN, or custom schedulers)
• Deep familiarity with GPU/accelerator scheduling challenges: gang-scheduling, topology-aware placement, preemption, hardware affinity constraints
• Experience defining and enforcing SLAs and resource guarantees for compute workloads
• Capacity planning experience across cloud and on-premises infrastructure
• Experience scaling through hypergrowth in compute-intensive environments (AI/ML, HPC, large-scale cloud infrastructure)
• Experience with observability and efficiency tooling for distributed infrastructure

Compensation & Benefits

• Annual Salary: $305,000–$385,000 USD