> Markdown version of [/jobs/ext/1429219-research-engineer-machine-learning](https://www.wearedevelopers.com/jobs/ext/1429219-research-engineer-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Research Engineer, Machine Learning

- **Company:** Mistral Inc
- **Location:** Palo Alto, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Code Review, Nvidia CUDA, Continuous Integration, Learning Management Systems, Distributed Computing Environment, Python (Programming Language), Machine Learning, Tensorflow, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Kubernetes, Information Technology, Slurm, Machine Learning Operations, Data Pipelines
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=edae36d0c0c10132

## About the Role

* Master's or PhD in Computer Science (or equivalent proven track record).

 * 4 + years working on large-scale ML codebases.

 * Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s).

 * Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops.

 * Strong software-design instincts: testing, code review, CI/CD.

 * Self-starter, low-ego, collaborative.

## Description

The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research production spectrum as needs or interests evolve.

As a Research Engineer - ML track, you'll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you'll either join:

 * Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or

 * Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, …) and turn fresh ideas into repeatable, scalable code.

What You Will Do

 * Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools.

 * Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs.

 * Conduct experiments on the latest deep-learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs).

 * Design, implement and benchmark ML algorithms; write clear, efficient code in Python.

 * Deliver prototypes that become production-grade components for Le Chat and our enterprise API.


## Related Videos

- [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes)
- [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning)
- [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)

## Related Articles

- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)