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Role Description

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

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.

As a Cohere Research Intern, you will:

• 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.

Qualifications

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

Preferred Qualifications

• 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 to tackle analytical problems using quantitative methodologies.
• Proficiency in handling and analysing complex, high-dimensional data from various sources.
• Experience in applying theoretical and empirical research to real-world problem-solving.

Benefits

• 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 up to 6 months
• 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 (30 working days!)