Machine Learning Intern/Co-op (Winter 2027)

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?

Ship state of the art models to production.

Design and implement novel research ideas.

Build elegant training/deployment pipelines.

Join us at a pivotal moment, shape what we build and wear multiple hats as an intern!

Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage

Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term.

As a Machine Learning Intern, you will:

• Design, train and improve upon cutting-edge models.
• Help us develop new techniques to train and serve models safer, better, and faster.
• Train extremely large-scale models on massive datasets.
• Explore continual and active learning strategies for streaming data.
• Learn from experienced senior machine learning technical staff.
• Work closely with product teams to develop solutions.