Member of Technical Staff, MLE

About the Role

This is not a typical "Applied Scientist" or "ML Engineer" role. As a Member of Technical Staff, Applied ML, you will work directly with enterprise customers on problems that push LLMs to their limits. You'll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. You will train and customize frontier models — not just use APIs — leveraging Cohere's full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Your work will directly influence the capabilities of Cohere's foundation models, shaping the next generation of frontier models. You will operate with an early-startup level of ownership inside a frontier-model company, combining the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab, while wearing multiple hats, setting a high technical bar, and defining what Applied ML at Cohere becomes.

What You'll Do

• Technical Leadership & Solution Design: Contribute to the design and delivery of custom LLM solutions for enterprise customers. Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies.
• Modeling, Customization & Foundations Contribution: Build custom models using Cohere's foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets. Develop SOTA modeling techniques that directly enhance model performance for customer use-cases. Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks.
• Customer-Facing Technical Impact: Work as part of Cohere's customer facing MLE team to identify high-value opportunities where LLMs can unlock transformative impact to our enterprise customers.

You May Be a Good Fit If You Have

• Technical Foundations: Strong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions. Fluency with Python and core ML/LLM frameworks. Experience working with (or the ability to learn) large-scale datasets and distributed training or inference pipelines. Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies. Demonstrated ability to meaningfully shape LLM performance.
• Experience & Leadership: A broad view of the ML research landscape and a desire to push the state of the art.
• Mindset: Bias toward action, high ownership, and comfort with ambiguity. Humility and strong collaboration instincts. A deep conviction that AI should meaningfully empower people and organizations.

Benefits

• 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. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming 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.