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Site Reliability Engineer, Inference Infrastructure

Cohere

Site Reliability Engineer, Inference Infrastructure

Cohere

Toronto

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Healthcare

Mental Health

Parental Leave

Free Meals

Learning Budget

Remote Work

Commuter Benefits

Healthcare

Mental Health

Parental Leave

Meals

Learning

Remote Work

Commuter

Required Skills

Kubernetes

Linux

Distributed Systems

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 ROLE?

Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for a Site Reliability Engineer to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs.

As a Site Reliability Engineer you will:

  • Build self-service systems that automate managing, deploying and operating services.

  • This includes our custom Kubernetes operators that support language model deployments.

  • Automate environment observability and resilience. Enable all developers to troubleshoot and resolve problems.

  • Take steps required to ensure we hit defined SLOs, including participation in an on-call rotation.

  • Build strong relationships with internal developers and influence the Infrastructure team’s roadmap based on their feedback.

  • Develop our team through knowledge sharing and an active review process.

You may be a good fit if you have:

  • 5+ years of engineering experience running production infrastructure at a large scale

  • Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters

  • Experience with Kubernetes dev and production coding and support

  • Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving

  • Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments

  • Experience in compute/storage/network resource and cost management

  • Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork

  • The grit and adaptability to solve complex technical challenges that evolve day to day

  • Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference.

  • Strong understanding or working experience with distributed systems.

  • Experience in Golang, C++ or other languages designed for high-performance scalable servers).

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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About 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

Employees

Toronto

Headquarters

$2.2B

Valuation

Reviews

3.8

45 reviews

Work Life Balance

3.6

Compensation

4.2

Culture

4.0

Career

3.8

Management

3.5

78%

Recommend to a Friend

Pros

Supportive team and management

Competitive compensation and benefits

Good work-life balance and flexible environment

Cons

Room for improvement in processes

Career progression could be clearer

Some organizational bureaucracy

Salary Ranges

0 data points

L2

L3

L4

L5

L6

Senior/L5

L2 · Solution Architect L2

0 reports

$71,230

total / year

Base

$28,492

Stock

$35,615

Bonus

$7,123

$49,861

$92,599

Interview Experience

8 interviews

Difficulty

3.1

/ 5

Duration

14-28 weeks

Offer Rate

25%

Experience

Positive 25%

Neutral 0%

Negative 75%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Take-home Assessment

5

Hiring Manager Interview

6

Final Round Interview

Common Questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design

Past Experience