Why This Job is Featured on The SaaS Jobs
Model-serving reliability has become a core differentiator for SaaS businesses commercialising AI through APIs, and this Site Reliability Engineer role sits directly on that fault line. The remit is tied to inference infrastructure, where latency, throughput, and availability translate quickly into product trust for developers and enterprise buyers. With an explicitly remote setup and a Toronto base, the listing signals a globally distributed operating model typical of modern SaaS platforms.
From a SaaS career perspective, the work maps to durable platform competencies: production Kubernetes operations, multi cloud deployment patterns, and SLO driven engineering that supports externally consumed services. The emphasis on self service automation and observability aligns with how SaaS teams scale reliability without scaling headcount linearly. Exposure to GPU backed workloads also adds a specialised layer that is increasingly relevant as more SaaS products embed model inference in core flows.
This role fits engineers who prefer owning operational outcomes end to end, including structured on call responsibilities, and who enjoy collaborating across internal teams to shape infrastructure roadmaps. It is well suited to someone comfortable with ambiguity in complex distributed systems and motivated by measurable service performance rather than feature delivery alone.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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, 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!)
