Member of Technical Staff, Post-Training

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!

Role Overview:

Advance the state of the art for model post training, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organisational needs. We have all the compute, data, and talent available for you to do your best work.

Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly!

Key Responsibilities:

Design and write high-performant and scalable software for training models.

Consistently post-train the models to reach SOTA level performance.

Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all encompassing performance.

Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime.

Research, implement, and experiment with ideas on our supercompute and data infrastructure.

Learn from and work with the best researchers in the field.

Qualifications:

Extremely strong software engineering skills.

Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.

Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray).

Experience using large-scale distributed training strategies.

Hands on experience on training large model at scale.

Hands on experience with the post training phase of model training, with a strong emphasis on performance optimisation.

Bonus : paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.