Member of Technical Staff, Integration/RL Team (Research Engineer)

Paris, FranceRemote

Responsibilities

- Develop new tools to support and accelerate research and LLM training.
- Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated post-training ecosystem.

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.
Join us on our mission and shape the future! The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods.
We strive for excellence in both engineering and science by meticulously designing experiments and design docs.
- Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR. -
Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray). - [Bonus] Hands-on
Experience in ML, LLM and RL academic research.
This role is perfect for you if you: - Have a deep passion for quality work. - Enjoy tuning and optimising large LLM models. - Comfortable working with people with different levels of software engineering skills, from beginner to more advanced. - Comfortable diving into complex ML codebases to identify and resolve issues, ensuring the smooth operation of our systems. - Thrive in a fast-paced, technically challenging environment, where you can contribute your innovative ideas and solutions.

Experience using and debugging large-scale distributed training strategies (memory/speed profiling). - [Bonus]
experience with the post-training phase of model training, with a strong emphasis on scalability and performance. - [Bonus]
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 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!)

Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.

Who are we? Our mission is to scale intelligence to serve humanity.
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.
While tasks are assigned according to everyone’s expertise, there is a global team effort to write production code and support the team research efforts, depending on individual interests and organizational needs.
In particular, this role aims to enhance the global quality of the post-training codebase by implementing new tools to ease and support research, optimizing post-training algorithms, and scaling distributed RL to unprecedented levels.
Please Note: We have offices in London, Paris, Toronto, San Francisco, New York but we are also remote-friendly! Applicants for this role may work anywhere between UTC−06:00 and UTC+01:00.
you will: - Design and write high-performing and scalable software for training models.