Build machine learning workload infrastructure remotely across Canada or the United States using Kubernetes, Python, or Go. Support Cohere’s foundation models.

As a Software Engineer on Internal Infrastructure, you will build platforms for training, evaluation, and reinforcement-learning workloads. You will work with AI researchers and ML engineers on stability, scalability, and observability. The work includes scheduling, networking, storage, and runtime isolation for Cohere’s North platform.

Key Responsibilities:

- Schedule training, evaluation, and reinforcement-learning jobs on Kubernetes
- Build workload networking, runtime isolation, agents, and sandboxes
- Coordinate storage for checkpoints and training artifacts
- Troubleshoot production failures and performance problems
- Develop automation,



infrastructure-as-code, and observability

Requirements:

- Production experience with job platforms, batch systems, or Kubernetes controllers
- Understanding of scheduling, queues, multi-tenant fairness, and distributed systems
- Experience with retries, partial failure, and automation judgment
- Software development experience in Python or Go
- Experience collaborating with researchers or ML engineers

Help operate Cohere’s machine learning platform through Kubernetes scheduling, distributed systems, workload networking, and observability.

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📌 Machine Learning Platform Software Engineer (Canada)
🏢 Wwshemi
📍 Canada