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# Research Engineer, Machine Learning

- **Company:** Mistral Inc
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Cluster Analysis, Code Review, Nvidia CUDA, Continuous Delivery, Continuous Integration, Learning Management Systems, Programming Tools, Distributed Computing Environment, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Software Engineering, Extensible Markup Language (XML), Scripting, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Kubernetes, Information Technology, Data Management, Slurm, Machine Learning Operations, Data Pipelines
- **Published:** September 21, 2026
- **Apply:** https://www.careerbuilder.com/job-details/research-engineer-machine-learning-palo-alto-ca--d00acce6-e778-4c05-a1ad-bd81204db660

## 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.
What We Offer, Algorithms, Application Programming Interface (API), Artificial Intelligence (AI), Benchmarking, CUDA (Compute Unified Device Architecture), Code Reviews, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Data Clustering, Data Management, Deep Learning, Embedded Systems, Finance, GPU (Graphics Processing Unit), Government, JAX (Java API for XML), Large-Scale Systems, Machine Learning, Machine Tool, Manufacturing, Natural Language Processing (NLP), Programming Tools, Public Health, Python Programming/Scripting Language, Scientific Research, Software Design, Team Player, Test Design

## Description

The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the researchproduction 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.


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