Member of Technical Staff, Senior/Staff MLE

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! WHY THIS ROLE IS DIFFERENT This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: 1. Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. 2. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. 3. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. 4. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. 5. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-f

Department: Modeling; Team: Applied-ML