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职位Cohere

Software Engineer, Internal Infrastructure (Europe & UK)

Cohere

Software Engineer, Internal Infrastructure (Europe & UK)

Cohere

United Kingdom

·

On-site

·

Full-time

·

1mo ago

福利待遇

Healthcare

Mental Health

Parental Leave

Remote Work

Meals

Learning

Home Office

Commuter

必备技能

Kubernetes

Go

Python

Infrastructure as Code

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 team?

The internal infrastructure team is responsible for building world-class infrastructure and tools used to train, evaluate and serve Cohere's foundational models. By joining our team, you will work in close collaboration with AI researchers to support their AI workload needs on the cutting edge, with a strong focus on stability, scalability, and observability. You will be responsible for building and operating Kubernetes GPU superclusters across multiple clouds. Your work will directly accelerate the development of industry-leading AI models that power Cohere's platform North.

We’re hiring software engineers at multiple levels. Whether you’re early in your career or a seasoned staff engineer, you’ll find opportunities to grow and make an impact here.

Please Note: All of our infrastructure roles require participating in a 24x7 on-call rotation, where you are compensated for your on-call schedule.

As a Software Engineer in the Internal Infrastructure team, you will:

  • Build and operate Kubernetes compute superclusters across multiple clouds

  • Partner with cloud providers to optimize infrastructure costs, performance, and reliability for AI workloads

  • Work closely with research teams to understand their infrastructure needs and identify ways to improve stability, performance, and efficiency of novel model training techniques

  • Design and build resilient, scalable systems for training AI models, focusing on creating intuitive user interfaces that empower researchers to self-serve to troubleshoot and resolve problems

  • Encourage software best practices across our company and participate in team processes such as knowledge sharing, reviews, and on-call

You may be a good fit if you:

  • Have deep experience running Kubernetes clusters at scale and/or scaling and troubleshooting Cloud Native infrastructure, including Infrastructure as Code

  • Have strong programming skills in Go or Python

  • Prefer contributing to Open Source solutions rather than building solutions from the ground up

  • Are self-directed and adaptable, and excel at identifying and solving key problems

  • Draw motivation from building systems that help others be more productive

  • See mentorship, knowledge transfer, and review as essential prerequisites for a healthy team

  • Have excellent communication skills and thrive in fast-paced environments

Bonus qualifications:

  • You've previously worked with ML training infrastructure and GPU workloads and have familiarity with RDMA networking

  • You have expertise to support and troubleshoot low level Linux systems

  • You have experience collaborating with research teams or machine learning engineers

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

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 https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, 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 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!)

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关于Cohere

Cohere

Cohere

Series C

Cohere Inc. is an American-Canada-based international technology company focused on artificial intelligence. Cohere specializes in large language models and AI products for regulated industries, particularly the finance, healthcare, manufacturing, and energy fields, as well as the public sector.

201-500

员工数

Toronto

总部位置

$2.2B

企业估值

评价

2.4

3条评价

工作生活平衡

2.0

薪酬

3.0

企业文化

1.5

职业发展

2.5

管理层

1.2

15%

推荐给朋友

优点

Comprehensive and challenging assessment process

Well-known company in the industry

Initially appeared as attractive opportunity

缺点

Unprofessional hiring managers

Toxic work environment

Poor management and leadership

薪资范围

13个数据点

Mid/L4

Mid/L4 · Analytics Engineer

1份报告

$117,173

年薪总额

基本工资

$90,100

股票

-

奖金

-

$117,173

$117,173

面试经验

1次面试

难度

4.0

/ 5

时长

14-28周

体验

正面 0%

中性 0%

负面 100%

面试流程

1

Application Review

2

Take Home Assessment

3

Technical Interview

4

Team Interview

5

Offer

常见问题

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design