The opportunity
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.
What you'll do
Build and maintain data pipelines for SFT, preference, and RL post-training data.
Own dataset quality, versioning, and reproducibility.
Turn research data recipes into production-grade, reusable components.
Scale model inference for data generation and model-based grading.
Design data formats and schemas that keep post-training datasets consistent and efficient to train on.
Collaborate with researchers and engineers to make sure data pipelines keep: pace with the needs of cutting-edge language models.
What they're looking for
- Strong software engineering skills.
- Experience designing and building large-scale data pipelines for machine: learning, ideally for LLM post-training.
- Track record of running distributed data processing and model inference at scale.
- Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour.
