Software Engineer, ML Workload Platform

AItoolnavio; Toronto; Hybrid; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Weekly lunch stipend

Health and dental benefits

RRSP matching

Parental Leave top-up

Education & learning stipend

6 weeks paid vacation

Travel budget to other offices

Home office stipend

Job summary

Cohere is seeking engineers to own and operate the platform that runs training, evaluation, and RL workloads on Kubernetes. You will ensure capacity, isolation, and reliable performance for AI research and production deployments.

You will collaborate with researchers and ML engineers, implement automation and IaC, and improve observability while supporting a 24x7 on-call rotation for platform reliability.

Qualifications

• Run a job platform, batch system, or Kubernetes controllers in production.

Responsibilities

• Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes.
• Build the networking and runtime isolation those workloads need.
• 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.

Skills

Kubernetes

Distributed systems

Python/Go

Observability

Job description

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 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.

How and Where We Work:

• Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening 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.

If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.