[Hiring] Engineering Manager, GPU Infrastructure @Cohere

Role Description

The GPU Clusters team is at the heart of Cohere's infrastructure, building and operating the superclusters that power our frontier AI models. We're not just managing hardware - we're enabling the research and development that defines what's possible with large language models. This team sits at the intersection of cutting-edge hardware, distributed systems, and AI research, working directly with cloud providers and researchers to solve challenges that few companies in the world are tackling.

As an Engineering Manager, you will:

• Team Leadership & Development
  • Lead and mentor a team of engineers specializing in GPU infrastructure, fostering a culture of technical excellence and continuous improvement.
  • Manage performance, career development, and hiring for team members.
  • Conduct regular 1:1s and team meetings to ensure alignment and address challenges.
  • Provide technical guidance and support to team members on complex infrastructure problems.
• Technical Strategy & Execution
  • Define and execute the technical roadmap for GPU cluster deployment, optimization, and scaling.
  • Oversee the implementation of topology-aware scheduling, hardware fault detection, and performance optimization systems.
  • Collaborate with cloud providers to validate and deploy new GPU architectures.
  • Ensure infrastructure reliability, scalability, and security across all GPU environments.
• Cross-Functional Collaboration
  • Partner with AI researchers to understand emerging infrastructure needs and translate them into robust solutions.
  • Work with the Foundations team on training software stack adaptation for new GPU architectures.
  • Coordinate with Capacity EPM on delivery timelines and resource planning.
  • Interface with Legal and Security teams on compliance requirements.
  • Collaborate with other infrastructure teams on shared goals and dependencies.
• Operational Excellence
  • Establish observability and monitoring frameworks for GPU utilization, performance, and reliability.
  • Implement infrastructure-as-code practices and automation for cluster provisioning.
  • Drive cost optimization initiatives while maintaining performance standards.
  • Manage vendor relationships and contract negotiations for hardware and cloud services.
  • Ensure documentation is comprehensive, up-to-date, and accessible to stakeholders.

Qualifications

• Experience managing engineering teams with a focus on technical mentorship and growth.
• Strong communication skills to translate complex technical concepts for diverse audiences.
• Ability to make data-informed decisions under pressure.
• Experience working in remote, distributed teams.
• Commitment to fostering an inclusive and collaborative team culture.
• Deep expertise in ML/HPC infrastructure: GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing environments.
• Proven experience with Kubernetes at scale: deployment, management, and troubleshooting cloud-native clusters for AI workloads in multi-cloud environments.
• Knowledge of infrastructure monitoring tools (Prometheus, Grafana).
• Familiarity with Terraform, ArgoCD, or other IaC tools.
• Experience with cost optimization and capacity planning for GPU infrastructure.
• Track record of collaborating with AI researchers or ML engineers to solve infrastructure challenges.

Personal Qualities

• Strong problem-solving abilities with a data-driven approach.
• Passion for enabling AI research through robust infrastructure.
• Collaborative mindset with a focus on cross-team success.
• Willingness to learn and adapt in a fast-paced, evolving environment.

Benefits

• 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.