Why This Job is Featured on The SaaS Jobs
Within the SaaS ecosystem, model efficiency work sits directly on the critical path between research capability and reliable, economical product delivery. A Staff Research Engineer focused on inference performance is positioned where infrastructure decisions translate into customer-facing latency, throughput, and cost tradeoffs, which are core constraints for AI-enabled SaaS offerings. The listing signals a company operating at the frontier-model layer, serving developers and enterprises rather than building a single vertical application.
From a SaaS career perspective, this kind of role builds durable leverage in production AI systems: profiling and optimizing real workloads, understanding GPU execution economics, and shipping improvements that affect service-level behavior at scale. Experience across the model execution stack tends to transfer across SaaS organizations adopting LLM features, because the same efficiency bottlenecks reappear in search, RAG, and agentic workflows. It also provides a bridge between research methods and platform engineering, a combination that remains scarce.
This role is best suited to engineers who prefer deep technical ownership, measurable performance outcomes, and iterative experimentation tied to production constraints. It fits professionals who want to operate close to deployment realities, collaborate across research and engineering boundaries, and influence how AI capabilities are packaged into dependable SaaS infrastructure.
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?
Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including:
model architecture and MoE routing optimization
decoding and inference-time algorithm improvements
software/hardware co-design for GPU acceleration
performance optimization without compromising model quality
Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations.
As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production.
You may be a good fit for the model efficiency team if you:
Have a PhD in Machine Learning or a related field
Understand LLM architecture, and how to optimize LLM inference given resource constraints
Have significant experience with one or more techniques that enhance model efficiency
Strong software engineering skills
An appetite to work in a fast-paced high-ambiguity start-up environment
Publications at top-tier conferences and venues (ICLR, ACL, NeurIPS)
Passion to mentor others
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!)
