# Product Manager, Compute Platform

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY, Seattle, WA
**Role:** Product Management
**Salary:** $305k – $385k/yr
**Experience:** 7+ years
**Skills:** Kubernetes, Slurm, Borg, Yarn, Gpu Scheduling, Job Scheduling, Resource Orchestration, Capacity Planning, Observability, Distributed Systems
**Posted:** 2026-06-05

> Product Manager owning compute platform strategy, job scheduling, and capacity management for Anthropic's GPU clusters. Requires 7+ years PM experience with infrastructure or distributed systems.

## Job Description

## 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

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