# Member of Technical Staff, MLE

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

> Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and contribute to foundation model improvements. Requires strong ML fundamentals, Python fluency, and experience with LLMs and large-scale data.

## Job Description

## Why This Role Is Different

As a Member of Technical Staff, Applied ML, you will:

- Work directly with enterprise customers on problems that push LLMs to their limits. Rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models.
- Train and customize frontier models using Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques.
- Influence the capabilities of Cohere’s foundation models with techniques, datasets, evaluations, and insights.
- Operate with early-startup ownership inside a frontier-model company.
- Wear multiple hats, set a high technical bar, and define Applied ML at Cohere.

## 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.

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**Canonical:** https://hotfix.jobs/jobs/629874ff-30ab-4dd2-8ae3-0a5e7ca579c4