Software Engineer, GPU Infrastructure

Company: Cohere

Location: Seattle (Remote)

Salary: $200k - $325k per year

Type: Full-time

Remote: Yes

Posted: 2026-11-06

About this role

## 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?

Internal Infrastructure builds the infrastructure and tools used to train, evaluate, and serve Cohere's foundation models. You will work with AI researchers and ML engineers on stability, scalability, and observability. The work accelerates the models behind Cohere's platform, North.

You will run the shared Kubernetes fleets those workloads land on: multi-cloud GPU and TPU clusters, node health, performance, and the partnership with cloud providers and hardware vendors. The role includes a compensated 24x7 on-call rotation.

### What you will do

  • Deploy and operate GPU Kubernetes clusters across clouds, and bring up new hardware generations and providers.
  • Work with cloud providers and hardware partners on reliability, performance, and cost, including RDMA and high-speed interconnects.
  • Automate node, GPU, and fabric fault detection and remediation so most faults are fixed without a human.
  • Improve fleet utilization, track cost, and cut the time it takes to get a faulty node back into service.
  • Troubleshoot production failures and performance problems, and leave the system easier to operate...

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