Offer summary

Qualifications:

Strong background in machine learning and natural language processing., Experience developing evaluation benchmarks and datasets for large language models., Proficiency in software engineering with a focus on AI tools and infrastructure., Research track record demonstrated by publications or benchmarks in LLM evaluation..

Key responsibilities:

Develop and improve evaluation benchmarks and datasets for LLMs.

Conduct research to advance evaluation methods and efficiency.

Build scalable tools to analyze and understand model evaluation results.

Collaborate with researchers and engineers to push the state-of-the-art in model evaluation.

Job description

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 realworld use cases, we must continue to develop new techniques to accurately measure our models performance on frontier capabilities. In this role, you are responsible for creating nextgeneration evaluation methods and scalable infrastructure to measure LLM progress.

As a Senior Research Engineer, Model Evaluation, you will:

Develop evaluation benchmarks, datasets, and environments for measuring the bleeding edge of model capabilities
Conduct research to push the stateoftheart in LLM evaluation methods, including training LLM judges; improving evaluation efficiency; and scalably building highquality datasets
Build scalable tools for investigating and understanding evaluation results that are used by all members of technical staff at Cohere, as well as leadership and our CEO
Learn from and work with the best researchers and engineers in the field