Research Engineer

Who We Are

Our mission is to scale intelligence to serve humanity. Cohere trains and deploys frontier models for developers and enterprises building AI systems that power magical experiences like content generation, semantic search, RAG, and agents. We believe our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each 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, 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!

About Cohere Labs

Cohere Labs is the dedicated research arm of Cohere. Our mission is to push machine learning forward through open, collaborative research and hands-on experimentation. We work on frontier problems in NLP and AI while creating space for researchers and engineers from different backgrounds to contribute, learn, and grow.

We care about building things that are both thoughtful and useful, from new methods and datasets to tools that make research more accessible. Our team values curiosity, ownership, and practical impact over hype.

Why Join Cohere Labs?

Cohere Labs brings together researchers and engineers to explore ambitious ideas and turn them into real systems. We focus on advancing machine learning while expanding access to applied research training and global collaboration.

Our Mission Approach

• Creating open, collaborative research spaces where engineers and researchers work side-by-side on ambitious ML problems.
• Expanding access to applied research training, helping early-career engineers grow into strong research contributors.

About the Research Engineer Role

We’re looking for Research Engineers who enjoy getting their hands dirty: building experiments, debugging models, scaling training pipelines, and turning research ideas into working systems.

This is a highly practical role. You’ll work closely with scientists and other engineers to implement new methods, run large-scale experiments, and help shape the infrastructure that supports our research programs.

You don’t need to have everything figured out yet. We care more about curiosity, strong fundamentals, and a willingness to learn quickly in a fast-moving research environment.

At Cohere Labs, Research Engineers are not just support roles. They are core contributors who help define how ideas become reality. If you want to work on meaningful problems, learn fast, and help build tools that shape the future of AI, we’d love to hear from you.

What We're Looking For

• Have a strong engineering background in machine learning, NLP, or related areas (through a Master’s degree, industry experience, or equivalent hands-on work).
• Enjoy writing clean, reliable code and building systems that others can use and extend.
• Are comfortable experimenting, running ablations, analyzing results, and iterating quickly.
• Have experience with deep learning frameworks and model optimization techniques (PyTorch, distributed training, RLHF, finetuning, evaluation frameworks).
• Like collaborating closely with researchers and translating ideas into practical implementations.
• Are excited to grow your research instincts while staying grounded in engineering excellence.

Cohere Employee 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 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!)

Key skills/competency

• Machine Learning Engineering
• Natural Language Processing (NLP)
• Deep Learning Frameworks (PyTorch)
• Model Optimization
• Distributed Training
• Experimentation & Ablation
• Debugging Models
• Scaling Training Pipelines
• Clean Code Development
• Research Collaboration