The internal infrastructure team is responsible for building world-class infrastructure and tools used to train, evaluate and serve Cohere’s foundational models
By joining our team, you will work in close collaboration with AI researchers to support their AI workload needs on the cutting edge, with a strong focus on stability, scalability, and observability
You will be responsible for building and operating superclusters across multiple clouds
Your work will directly accelerate the development of industry-leading AI models that power Cohere’s platform North
Build and scale ML-optimized HPC infrastructure: Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads
Optimize for AI/ML training: Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance, leveraging technologies like RDMA, NCCL, and high-speed interconnects
Troubleshoot and resolve complex issues: Proactively identify and resolve infrastructure bottlenecks, performance degradation, and system failures to ensure minimal disruption to AI/ML workflows
Enable researchers with self-service tools: Design intuitive interfaces and workflows that allow researchers to monitor, debug, and optimize their training jobs independently
Drive innovation in ML infrastructure: Work closely with AI researchers to understand emerging needs (e.g., JAX, PyTorch, distributed training) and translate them into robust, scalable infrastructure solutions
Champion best practices: Advocate for observability, automation, and infrastructure-as-code (IaC) across the organization, ensuring systems are maintainable and resilient
Mentorship and collaboration: Share expertise through code reviews, documentation, and cross-team collaboration, fostering a culture of knowledge transfer and engineering excellence
Benefits
Six weeks’ paid vacation
Equity / stock options
RRSP, 401(k), and Pension Scheme contributions
Coverage for 100% of your insurance premiums across health, dental, vision, and travel
Additional coverage for accessing mental health providers/services
Six months of fully paid parental leave, including adoption and surrogacy
Financial support for egg freezing and IVF in Canada and the UK
A monthly fitness and wellness allowance
Globally dispersed company that supports a remote work culture
A $2,000 annual education benefit for professional development
A weekly stipend for meals when working remotely and catered lunch when working from one of our global offices
A monthly arts and culture allowance
A monthly quality time allowance- Self-directed problem-solving: The ability to identify bottlenecks, propose solutions, and drive impact in a fast-paced environment
Low-level systems knowledge: Familiarity with Linux internals, RDMA networking, and performance optimization for ML workloads
Kubernetes at scale: Proven ability to deploy, manage, and troubleshoot cloud-native Kubernetes clusters for AI workloads
Research collaboration experience: A track record of working closely with AI researchers or ML engineers to solve infrastructure challenges
Deep expertise in ML/HPC infrastructure: Experience with GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing (HPC) environments
Strong programming skills: Proficiency in Python (for ML tooling) and Go (for systems engineering), with a preference for open-source contributions over reinventing solutions
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!
