Senior Research Scientist, Model Evaluation

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 co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us! Why this role? Evaluation is critical to making progress in scaling intelligence. As models continue to become superhuman in many real-world use cases, we must continue to develop new evaluation techniques that accurately reflect what models are already capable of, as well as set the agenda for what future models should be capable of. In this role, you are responsible for creating these next-generation evaluation methods and infrastructure to measure LLM progress. As a Senior Research Scientist, Model Evaluation, you will: • Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish. • Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations. • Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency. • Build scalable and reusable tools for digging into model performance. You may be a good fit if: • You enjoy rapidly building prototypes that demonstrate the boundaries of what LLMs are capable of, and you have developed resources to measure those capabilities. • You have spent dozens of hours reviewing complex data and LLM outputs to ensure high data quality. • You are obsessive about rigorously measuring AI capabilities, and also about making sure your measurements actually align with the capabilities you care about. • You have strong software engineering skills. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: • A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. • Full health and dental benefits, including a separate budget for mental health. • RRSP matching, 401K, Pension Scheme. • 100% Parental Leave top-up for up to 6 months, for either parent. • Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. • 6 weeks of paid vacation (30 working days!) • Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: • Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon. • For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. • For those not near an office: a co-working benefit so you can work alongside others in your city. • Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.