Member of Technical Staff, Senior/MLE
Listed on 2026-01-11
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
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 Is DifferentThis 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.
Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post‑training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques.
Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models.
Operate with an early‑startup level of ownership inside a frontier‑model company. This role combines the breadth of an early‑stage CTO with the infrastructure and scale of a deep‑learning lab.
Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer‑facing engineering, and core‑model influence as directly as this one.
Technical Leadership & Solution Design
Lead 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 closely with enterprise customers to identify high‑value opportunities where LLMs can unlock transformative impact.
Provide technical leadership across discovery, scoping, modeling, deployment, agent workflows, and post‑deployment iteration.
Establish evaluation frameworks and success metrics for custom modeling engagements.
Team Mentorship & Organizational Impact
Mentor engineers across distributed teams.
Drive clarity in ambiguous situations, build alignment, and raise engineering and modeling quality across the organization.
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 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
Experience engaging directly with customers or stakeholders to design and deliver ML‑powered solutions.
A track record of technical leadership at a team level.
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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).