ML Workload Platform Engineer - Kubernetes & Pipelines

Cohere; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Weekly lunches

Job summary

Cohere, a security-first enterprise AI company, is looking for an engineer to own the Kubernetes-based platform that schedules and runs ML training, evaluation, and RL workloads. You’ll ensure stability, scalability, and observability to support researchers and ML engineers building the platform.

You may be a good fit if you have hands-on production experience with job platforms or Kubernetes controllers, strong distributed-systems judgment, and proficiency in Python or Go.

Qualifications

• Run a job platform, batch system, or Kubernetes controllers in production.
• Scheduling, queues, and multi-tenant fairness are central to this work.
• Experience with ML training workflows, RL sandboxes, container networking at scale is a plus.
• Proficiency in Python or Go and contributing to open-source projects is valued.

Responsibilities

• Own the platform that schedules and runs training, evaluation, and reinforcement-learning jobs on Kubernetes.
• Build networking and runtime isolation for workloads.
• Work with data infra on storage for checkpoints and artifacts.
• Troubleshoot production failures and improve operability.
• Build automation and observability to maintain the platform.

Skills

Kubernetes

Python

Go

Distributed systems

On-call rotation

Job description

Cohere, a security-first enterprise AI company, is looking for an engineer to own the Kubernetes-based platform that schedules and runs ML training, evaluation, and RL workloads. You’ll ensure stability, scalability, and observability to support researchers and ML engineers building the platform.

You may be a good fit if you have hands-on production experience with job platforms or Kubernetes controllers, strong distributed-systems judgment, and proficiency in Python or Go.