Who are we?

Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

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. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

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.

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

We value and celebrate diversity and 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, and we will work together to meet your needs.

Full-Time Employees At Cohere Enjoy These Perks

🤝 An open and inclusive culture and work environment

🧑‍💻 Work closely with a team on the cutting edge of AI research

🍽 Weekly lunch stipend, in-office lunches & snacks

🦷 Full health and dental benefits, including a separate budget to take care of your mental health

🐣 100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK

🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement

🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend

✈️ 6 weeks of vacation

Note: This post is co-authored by both Cohere humans and Cohere technology.

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.