Advance model post-training with Python and large-scale distributed training at Cohere, working remotely or from listed offices. Ship frontier models into production.

As a Member of Technical Staff, you will bridge research and production while advancing model post-training. You will write production software, support research, and collaborate across specialist teams. The work spans SFT, RL, supercompute, and data infrastructure.

Key Responsibilities:

- Design scalable software for model training
- Post-train models toward state-of-the-art performance
- Coordinate with Agentic and Code specialist teams
- Improve SFT and RL training cycles
- Experiment on supercompute and data infrastructure

Requirements:

- Extremely solid software engineering skills
- Proficiency in Python, JAX, PyTorch, and XLA/MLIR
- Experience with Kubernetes, Slurm, and Ray
- Experience using large-scale distributed training strategies
- Hands-on experience training large models at scale

Build production machine learning systems while optimizing post-training performance across Cohere’s research and engineering efforts.

📌 Machine Learning Software Engineer (Toronto)
🏢 Cohere
📍 Toronto