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Software Engineer, ML Workload Platform

Cohere · Canada
✨ Reading the job post and pulling out the key points…
Full job post · as written by Cohere

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 build the platform that runs training, evaluation, and reinforcement-learning workloads: job lifecycle, scheduling, workload networking, and the storage those jobs depend on. The role includes a compensated 24x7 on-call rotation.

WHAT YOU WILL DO

  • Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes: who gets capacity, what happens when a job fails, and how a researcher finds out whether the platform caused it.
  • Build the networking and runtime isolation those workloads need, including agent and sandbox environments.
  • Work with the data infrastructure team on storage for checkpoints and other training artifacts.
  • Troubleshoot production failures and performance problems, and leave the system easier to operate than you found it.
  • Build automation, infrastructure-as-code, and observability so the platform stays maintainable.

We hire at more than one level. We set level based on the scope you've owned and how independently you drive work.

YOU MAY BE A GOOD FIT IF YOU HAVE

  • Run a job platform, batch system, or Kubernetes controllers in production. Scheduling, queues, and multi-tenant fairness are central to this work.
  • Shown distributed systems judgment: retries, partial failure, and knowing what not to automate.
  • Worked on ML training workflows, RL sandboxes, container networking (CNI), or checkpoint storage at scale. Direct GPU-cluster experience is a plus.
  • Written software in Python or Go. You would rather extend a solid open-source project than rebuild it.
  • Worked with researchers, ML engineers, or another team whose goals were not identical to yours.
  • Found a bottleneck, proposed a fix, and driven it in a fast-moving environment.

If this does not line up exactly with your experience, we still encourage you to apply.

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…

Apply on Cohere's site ↗Opens Cohere's official careers page. Your application goes straight to them.
Company
Cohere
Location
Canada
Work mode
Remote
Salary
$175K - $325K
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Apply on Cohere's site ↗Opens Cohere's official careers page. Your application goes straight to them.

Overview

Build and maintain the ML workload scheduling platform on Kubernetes for Cohere's enterprise AI team.

Skills

KubernetesPythonGoCNIML trainingRL sandboxCheckpoint storageGPU cluster

Responsibilities

  • Own scheduling and execution of training, evaluation, and RL jobs on Kubernetes.
  • Design networking and runtime isolation for multi‑tenant ML workloads.
  • Integrate with data infrastructure for checkpoint and artifact storage.
  • Diagnose and resolve production failures and performance issues.
  • Build automation, IaC, and observability for platform maintainability.
  • Participate in on‑call rotation to support 24x7 service.

Requirements

  • 3+ years running production job platforms or Kubernetes controllers.
  • Strong distributed systems judgment: retries, partial failures, automation limits.
  • Experience with ML training pipelines, RL sandboxes, or GPU cluster usage.
  • Proficiency in Python or Go; extend open-source projects.
  • Collaboration with researchers or ML engineers on differing goals.

About Cohere

Cohere builds foundation AI models for security-first enterprise solutions.

What to prepare

Kubernetes schedulingDistributed systems resilienceML workflow engineeringObservability
Summarised by AI from the job post. Check the full post before applying.