Engineering Manager, GPU Infrastructure

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this team? The GPU Clusters team builds and operates the superclusters that train Cohere’s frontier models. We sit at the intersection of hardware, distributed systems, and AI research. We work with cloud providers, researchers, and other infrastructure teams on problems few companies get to take on. 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. As an Engineering Manager, you will: 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 You may be a good fit if you have: 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 Full-Time Employees at Cohere enjoy these Perks: A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. Full health and dental benefits, including a separate budget for mental health. RRSP matching, 401K, Pension Scheme. 100% Parental Leave top-up for up to 6 months, for either parent. Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. 6 weeks of paid vacation (30 working days!) Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. For those not near an office: a co-working benefit so you can work alongside others in your city. Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers page.

Lead and mentor a team of engineers to build and operate superclusters that power frontier AI models. Define the technical roadmap for GPU cluster deployment, optimization, and scaling while collaborating with AI researchers and cloud providers.

Requires deep expertise in ML/HPC infrastructure, Kubernetes at scale, and experience managing engineering teams. Candidates should be proficient with IaC tools and have a track record of solving complex infrastructure challenges for AI workloads.

• Weekly Lunch Stipend • Health Benefits • Dental Benefits • Mental Health Budget • RRSP Matching • 401K • Pension Scheme • Parental Leave Top-up • Annual Enrichment Benefits • Education And Learning Stipend • Paid Vacation • Travel Budget • Home Office Stipend

• KubernetesPreferred
• TerraformPreferred

Identified from the job description. Confirm important requirements above.

• Engineering Management
• GPU Infrastructure
• ML/HPC Infrastructure
• Kubernetes
• Distributed Training Frameworks
• Infrastructure As Code
• Capacity Planning
• Cost Optimization
• Technical Mentorship
• Cloud-Native Clusters
• Prometheus
• Grafana
• Terraform
• ArgoCD
• Distributed Systems
• Performance Optimization
• Technical Strategy
• Cross-Functional Collaboration
• Large Language Modeling
• Cloud-Native Computing
• Argo CD
• Workplace Inclusivity
• Business Problems
• Cloud Services
• Multi-Cloud
• Distributed Machine Learning
• Observability
• AI Research
• AI Adoption
• Willingness To Learn
• Infrastructure as Code (IaC)
• Self-Motivation
• Research
• Artificial Intelligence
• Automation
• Mental Health
• Management
• IT Capacity Management
• Communication
• Continuous Improvement Process
• Contract Negotiation
• Virtual Teams
• Leadership
• Scalability
• Innovation
• Problem Solving
• Machine Learning
• Mentorship
• Operational Excellence
• TensorFlow

• Engineering
• Technology
• Management & Leadership
• Software
• Data & Analytics
• Infrastructure Engineering Manager
• Engineering Manager (General)
• Manufacturing Managers
• Architectural and Engineering Managers

Minimum experience

10+ years

Posting language

English

Working hours

40 hours per week