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# Engineering Manager, GPU Infrastructure

- **Company:** COHERE, LLC
- **Location:** San Francisco, CA, United States (Remote available)
- **Salary:** $156,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Distributed Systems, Graphics Processing Unit (GPU), Multi-Cloud, Kubernetes, Hardware Infrastructure
- **Published:** October 26, 2026
- **Apply:** https://www.careerbuilder.com/job-details/engineering-manager-gpu-infrastructure-san-francisco-ca--cf8e25c3-98a6-4e00-8777-3f3af6579bdc

## About the Role

* Experience managing engineering or SRE teams, with a focus on technical mentorship, hiring, and growth, including in remote, distributed settings
 * A background running large Kubernetes compute fleets in production, including in multi-cloud environments: multi-cluster operations, scheduling, node health at scale, and familiarity with IaC and infrastructure monitoring
 * You've gone deep in one of the layers that make a GPU training fleet work, whether that's cluster-wide operations, GPU networking, or hardware, and you're willing to get hands-on and learn the rest
 * Experience with cost optimization and capacity planning for GPU infrastructure
 * A track record of partnering with researchers or ML engineers, and of making data-informed tradeoffs across reliability, cost, and delivery

## Description

As an Engineering Manager, you'll lead a team of engineers who care deeply about GPU infrastructure. You'll set technical direction, grow people, and help the company scale a rapidly growing compute footprint., * Hire, mentor, and grow a team of GPU infrastructure engineers, including performance, career development, and technical guidance on hard infrastructure problems

 * Own the technical roadmap for the fleet: how we deploy, operate, and scale Kubernetes clusters, including workload scheduling, hardware fault detection, and performance
 * Partner with researchers and ML engineers so the training and inference stack works well on new GPU architectures
 * Work with cross-functional stakeholders such as Capacity, Finance, Legal, Security, and other infrastructure teams on planning, cost, compliance, and shared dependencies
 * Drive operational excellence: observability for GPU utilization and reliability, automation of cluster provisioning, cost optimization, and vendor relationships