Member of Technical Staff, MLE
Quick Summary
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.
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!
This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will:
Responsibilities
~1 min read- →
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.
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.
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.
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.
A broad view of the ML research landscape and a desire to push the state of the art.
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.
This is a pivotal moment in Cohere’s history. As an MTS in Applied ML, you will define not only what we build — but how the world experiences AI. If you're excited about building custom models, solving generational problems for global organizations, and shaping frontier-model capabilities, we’d love to meet you.
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.
What We Offer
~1 min read🤝 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!)
Location & Eligibility
Listing Details
- Posted
- January 6, 2026
- First seen
- May 6, 2026
- Last seen
- May 9, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 21%
- Scored at
- May 6, 2026
Signal breakdown
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