技术成员，集成/RL 团队（研究工程师）
Member of Technical Staff, Integration/RL Team (Research Engineer)
我们是谁？
Cohere 是一家以安全为首要任务的企业级人工智能公司。我们构建前沿的基础人工智能模型和端到端产品，旨在解决现实世界中的商业问题。
我们正在为正在构建人工智能系统的企业的训练和部署前沿模型。我们认为我们的工作对人工智能的广泛应用至关重要，我们正在寻找希望成为其中一员的人才。
我们对所构建的东西非常执着。我们每个人都负责提升模型的能力以及为客户创造的价值。Cohere 是一个由研究人员、工程师、设计师等组成的团队，他们对各自的专业充满热情。
我们是一家总部位于多伦多的全球科技公司，在伦敦、纽约市、旧金山、蒙特利尔、巴黎、柏林和首尔设有主要办事处。加入我们！
职位概述：
集成团队负责开发和扩展用于大语言模型（LLM）后训练的机器学习算法和基础设施，重点在于大规模、分布式强化学习（RL）方法。我们通过精心设计实验和设计文档，在工程和科学方面追求卓越。虽然任务根据每个人的专长进行分配，但根据个人兴趣和组织需求，团队会共同努力编写生产代码并支持团队研究工作。
特别是，这个职位的目标是通过实施新工具来简化和支持研究，优化后训练算法，并将分布式强化学习扩展到前所未有的水平，从而提高后训练代码库的全局质量。
注意事项：我们在伦敦、巴黎、多伦多、旧金山和纽约设有办公室，但我们也支持远程办公！申请此职位的候选人可以在 UTC−06:00 至 UTC+01:00 之间的任何地方工作。
主要职责：
- 设计并编写高性能且可扩展的模型训练软件。
- 开发新工具以支持和加速研究和 LLM 训练。
- 与其他工程团队（基础设施、效率、服务）和科学团队（代理、多模态、多语言等）协调，创建强大且集成的后训练生态系统。
- 设计并实现技术以提高性能并加快我们的训练周期，包括 SFT、离线偏好和强化学习机制。
- 在我们的集群和数据基础设施上进行研究、实现和实验。
- 与其他科学家协作、协作、再协作
查看英文原文
Who are we?
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
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. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
Role Overview:
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. 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.
Key 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 the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated post-training ecosystem.
- Craft and implement techniques to improve performance and speed up our training cycles, both on SFT, offline preference, and the RL regime.
- Research, implement, and experiment with ideas on our cluster and data infrastructure.
- Collaborate, Collaborate, and Collaborate with other scientists, engineers, and teams!
Qualifications:
- Extremely strong software engineering skills.
- Value test-driven development methods, clean code, and strive to reduce technical debts at all levels.
- Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR.
- Experience using and debugging large-scale distributed training strategies (memory/speed profiling).
- [Bonus] Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray).
- [Bonus] Hands-on experience with the post-training phase of model training, with a strong emphasis on scalability and performance.
- [Bonus] 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.
Working Location:
This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.
FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Annual enrichment benefits:
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
HOW AND WHERE WE WORK:
- Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We 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 https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.