Staff Software Engineer, Inference Infrastructure

Cohere; San Francisco, New York (CA, NY); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Lunch stipend

Health and dental benefits

RRSP matching / 401K

Parental Leave

Education stipend

Vacation 6 weeks

Office/remote travel budget

Home office stipend

Job summary

Cohere is seeking Members of Technical Staff to join the Model Serving team in San Francisco. You will help build and operate the AI platform delivering large language models through easy-to-use API endpoints.

Ideal candidates have 5+ years of engineering in production infrastructure, experience with Kubernetes, cloud platforms, and high-performance distributed systems. This role is remote-friendly with office options in SF and travel per policy.

Qualifications

• 5+ years of engineering experience running production infrastructure at a large scale.
• Experience designing large, highly available distributed systems with Kubernetes.
• Experience with multi-cloud deployments (GCP, Azure, AWS) and on-prem/hybrid setups.
• Proficient in Linux-based compute environments and resource management.
• Strong collaboration and troubleshooting skills for mission-critical systems.

Responsibilities

• Develop, deploy, and operate the AI platform delivering Cohere's large language models through API endpoints.
• Collaborate with multiple teams to deploy optimized NLP models to production with low latency and high throughput.
• Ensure high availability and reliability of production services across clusters and clouds.
• Interface with customers to design customized deployments meeting their needs.

Skills

Production infrastructure

Kubernetes

Distributed systems

Cloud platforms

Linux

GPU workloads

Go/C++

Performance tuning

Troubleshooting

Job description

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!

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 Members of Technical Staff 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.

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).

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.

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, 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.