North is Cohere’s AI workspace platform for enterprises: a secure, customizable environment where companies can use AI across their real workflows while maintaining control over sensitive data. North connects AI agents with workplace tools, applications, and business context, helping users delegate complex work, build automations, inspect outputs, and collaborate with AI in production environments.
As North becomes more capable, one of the most important questions is also one of the hardest: how do we know whether the model is actually getting better for the workflows customers care about?
This role is about being the voice of North inside modelling. You will build the evaluation systems, feedback loops, and applied modelling workflows that make sure model progress translates into better product outcomes for North users. You will work closely with North product teams, customer-facing teams, and modelling teams to define what “good” means across the product surface, turn real usage and product direction into high-quality evals, and use those evals to guide model selection, patches, and regular model updates.
This is neither a pure research role nor a conventional product engineering role. It is a rigorous applied MLE role for someone who cares deeply about measurement, model behavior, and real-world product quality. You should be excited by the craft of building careful evals: evals that capture messy agentic workflows, reflect actual customer needs, resist superficial benchmark hacking, and provide useful signal for where the product and models need to go next.
Please note: this team works closely across Europe and East Coast North America time zones. We are open to candidates who can collaborate effectively within those hours.