Safety Research Internship; Spring​/Summer

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!

To have the opportunity to collaborate with Cohere’s Modelling Safety team on implementing novel research ideas that are grounded in real usage and real production models. We are broadly interested in the areas of:

• Fairness
• Safety: overall, but especially for multiple languages, dialects, and cultural contexts
• Robustness
• Generalisation
• Interpretability
• Safety for agents with complex read/write actions
• Safety for codegen

If there is any area you would like to work on not covered by this, please feel free to propose it, that can succeed! To increase chances of success, we would recommend you familiarise yourself with the publications of the team to get signal on whether your topic is something we might be interested in.

The goal of an internship will be to publish a paper in a top venue and make a contribution to open science. Many internship projects do also make it into our production systems and influence our model development, though this is not a requirement, just a bonus. Your project details and topic will be collaboratively designed between you and the team.

Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months.

This role can be remote. We do allow and encourage working out of one of Cohere’s office locations, but do not provide relocation or housing if you are not already nearby.

• Conduct cutting-edge machine learning research, training and evaluating production large language models.
• Focus on research projects aimed at making models better understood, safer, more reliable, more inclusive, and more beneficial for the world
• Disseminate your research results through the production of publications, datasets, and code.
• Contribute to research initiatives that have practical applications in Cohere’s product development.

• Are currently pursuing, or in the process of obtaining, a PhD in Machine Learning, NLP, Artificial Intelligence, or a related discipline. We will also consider exceptional non-PhD candidates.
• Are eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.
• Have experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models.
• Are familiar with autoregressive sequence models, such as Transformers.
• Have strong communication and problem-solving skills with the ability to convey complex research findings clearly and succinctly.
• Have knowledge, or are knowledgeable, of programming languages such as Python, C, C++, Lua, or related languages.
• Have knowledge of related ML frameworks such as JAX, Pytorch and Tensorflow.
• Have previous experience in building systems based on machine learning and deep learning techniques.
• Demonstrate passion for applied NLP models and products.

• Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
• Proven ability…