# Member of Technical Staff, Senior/Staff MLE

**Company:** [Cohere](https://hotfix.jobs/companies/cohere)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Skills:** Python, LLMs, Machine Learning, Cpt, Post-Training, Rlvr, Distributed Training, Model Evaluation, Large-Scale Datasets, Llm Architectures
**Posted:** 2026-01-06

> Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and influence foundation model capabilities. Requires strong ML fundamentals, Python fluency, and customer-facing technical leadership.

## Job Description

## Why This Role Is Different

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.
- 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.

## What You’ll Do

**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.

## 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 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 meaningfully empower people and organizations.

**Perks**
- Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
- Full health and dental benefits, including mental health budget
- 100% Parental Leave top-up for up to 6 months
- 6 weeks of vacation

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