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?
Cohere For AI (C4AI) is the dedicated research arm of Cohere. We work at the frontier of AI progress with the goal of solving cutting-edge scientific problems. We see contributions to top-tier conferences and publications in journals as an important part of our work, but also drive the creation of new research spaces and breakthroughs that change where, how and by whom research is done. Our mission is to solve complex machine-learning problems at the edge of what is currently technically possible. Cohere For AI has both a full-time research staff which builds the next generation of large scale machine learning models and an open science initiative that supports collaborative research across institutions and creates paths of access for independent researchers.
In this role, as a Machine learning Engineer, you work mainly on creating great libraries and usability for open research releases. This includes trained models, large-scale datasets, tools/libraries, and accessible walk-throughs of scientific research and technical breakthroughs. You are excited to be creative and create artifacts that make research models and open weights accessible to users and contributors of the broad open-source machine-learning ecosystem.
An essential aspect of this role is engaging with the wider open-source ML ecosystem, interacting with and learning from its users and contributors. Your responsibilities will include collaborating with researchers, ML practitioners and data scientists, making our research models accessible and intuitive to use on Huggingface, Kaggle answering queries and encouraging contributions and research extensions to released work via GitHub and our open science community.
Please Note: We have offices in Toronto, New York, San Francisco, and London but embrace being remote-first! There are no restrictions on where you can be located for this role.
As a machine learning engineer focused on open source, you will:
You may be a good fit if you:
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you consider yourself a thoughtful worker, a lifelong learner, and a kind and playful team member, Cohere is the place for you.
We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants of all kinds and are committed to providing an equal opportunity process. Cohere provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.
Our 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, Palo Alto, San-Francisco and London and co-working stipend
✈️ 6 weeks of vacation
Note: This post is co-authored by both Cohere humans and Cohere technology.