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?
We’re looking for an experienced machine learning researcher / engineer who can help us push the frontiers of agentic LLM systems.As a part of the team, you will help drive exploration and development of agentic techniques and have the opportunity to build the models that power our agentic solutions. Agentic LLM systems are being deployed widely across enterprise companies including through Cohere’s North platform. In this role, you’ll be working with a team developing new strategies for training models for advanced agent capabilities including reasoning, tool use, and memory. This includes developing data-generation techniques for post-training (SFT and RL*) Cohere’s models. Model advancements have direct impacts on North and other Cohere products creating an exciting opportunity where core model development leads to direct product advancements.
Please Note: We have offices in London, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! Our preference for this role is that you are based in Eastern Time, New York office, remote or hybrid works!
As a Member of Technical Staff for Agents Modeling you will:
Design and develop novel agentic solutions
Improve upon SOTA on hard agentic tasks
Research the next-generation of on-line learning-from-experience self-improvement
Work with partner teams (Reasoning, Post-training, Pre-training, etc.) to improve performance of agentic system
Work with an amazing team of researchers and engineers pushing the boundaries
You may be a good fit if you have:
Have a PhD in computer science or related field or similar industry research experience
Strong software engineering skills
Proficiency in Python and experience with ML-related code (e.g., pytorch, numpy, etc.)
Experience with LLMs and agentic frameworks
Experience with post-training LLMs (SFT, PEFT, or RL*)
Experience with building synthetic data generation pipelines
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, Cohere is the place for you.
We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
Full-Time Employees at Cohere enjoy these 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, New York, 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.
