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

Cohere

Montreal

Hybrid

CAD 80,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Open and inclusive work environment

Weekly lunch stipend

Full health and dental benefits

Parental leave top-up

Personal enrichment benefits

Remote-flexible work

6 weeks of vacation

Job summary

A leading AI research company in Montreal seeks a Member of Technical Staff to develop and scale machine learning algorithms. The role requires strong software engineering skills and proficiency in Python and ML frameworks. The ideal candidate will collaborate with engineering teams and contributes to innovative LLM training methods. The position offers competitive benefits, including extensive parental leave and a remote-friendly work culture.

Qualifications

Extremely strong software engineering skills.
Value test-driven development, clean code, and reducing technical debt.
Proficiency in Python and ML frameworks.

Responsibilities

Design and write high-performing and scalable software for training models.
Develop new tools to support and accelerate research and LLM training.
Coordinate with other engineering and scientific teams.

Skills

Software engineering skills

Test-driven development

Proficiency in Python

Experience with ML frameworks

Distributed training strategies

Tools

JAX

PyTorch

Kubernetes

Ray

Job description

Overview

Member of Technical Staff, Integration/RL Team (Research Engineer) – join Cohere to apply for this role.

About Cohere

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 and strive to increase the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more who are passionate about their craft, with a diverse range of perspectives as a requirement for building great products. Join us on our mission and shape the future.

Role and Team

The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, focusing on large-scale, distributed RL methods. Tasks are assigned by expertise, with a global team effort to write production code and support research efforts, depending on interests and organizational needs. 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.

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.

Responsibilities

Design and write high-performing and scalable software for training models.
Develop new tools to support and accelerate research and LLM training.
Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong, integrated post-training ecosystem.
Craft and implement techniques to improve performance and speed up training cycles, including SFT, offline preference, and RL regimes.
Research, implement, and experiment with ideas on cluster and data infrastructure.
Collaborate with scientists, engineers, and teams to support research and product goals.

Qualifications / Ideal Candidate

Extremely strong software engineering skills.
Value test-driven development, clean code, and reducing technical debt.
Proficiency in Python and ML frameworks such as JAX, PyTorch and/or XLA/MLIR.
Experience with large-scale distributed training strategies (memory/speed profiling).
Bonus: distributed training infrastructures (Kubernetes) and frameworks (Ray).
Bonus: hands-on experience with the post-training phase of model training, with emphasis on scalability and performance.
Bonus: experience in ML, LLM and RL academic research.

This Role Is Perfect For You

Have a deep passion for quality work.
Enjoy tuning and optimizing large LLM models.
Comfortable working with people at different levels of software engineering skill.
Able to dive into complex ML codebases to identify and resolve issues.
Thrive in a fast-paced, technically challenging environment and contribute innovative ideas.

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.

Perks

Full-Time employees enjoy an open and inclusive culture and work environment.
Work 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 for mental health.
100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK.
Personal enrichment benefits toward arts and culture, fitness and well-being, and workspace improvement.
Remote-flexible, offices in Toronto, New York, San Francisco and London, plus co-working stipend.
6 weeks of vacation.

Note: This post is co-authored by both Cohere humans and Cohere technology.

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