About the Role
Cohere is the leading security-first enterprise AI company, building cutting-edge foundation AI models and end-to-end products to solve real-world business problems. We are training and deploying frontier models for enterprises building AI systems, believing our work is instrumental to the widespread adoption of AI. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. 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 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 here, you'll lead a team of highly motivated engineers who are passionate about GPU infrastructure and AI. You'll be part of a collaborative, remote-first culture that values technical excellence, innovation, and impact. This is a unique opportunity to shape the infrastructure that will power the next generation of AI while working with exceptional technical talent dedicated to advancing the field.
Responsibilities
- 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 workload scheduling and queuing, hardware fault detection, and performance optimization systems
- Collaborate with cloud providers and MLEs to adapt our training and inference stack to bleeding-edge 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 research teams on training software stack adaptation for new GPU architectures
- Coordinate with Capacity EPM and Finance to manage capacity of a rapidly growing compute footprint
- 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
- Drive practices and policies to automate cluster provisioning and management
- Drive cost optimization initiatives while maintaining performance standards
- Manage vendor relationships and contract negotiations for hardware and cloud services
Leadership & Management Skills
- Experience managing engineering or SRE 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
Technical Expertise
- 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.
- Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming 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.