ML Research Engineer – Large-Scale Training

Mistral; Paris; On-site; EUR 90,000 - 150,000; Full time

Job summary

Mistral is seeking a Research Engineer - ML track in Paris to build and optimize large-scale learning systems. You will collaborate with Research Scientists to move ideas from research to production across platforms and embedded squads.

You'll implement robust ML tools, experiment with cutting-edge deep learning techniques, and write clear, efficient Python code. This role offers an opportunity to shape open-weight models powering enterprise AI solutions.

Qualifications

• 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.

Responsibilities

• 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.

Skills

PyTorch

JAX

TensorFlow

Distributed training

Software design

Collaboration

Education

Master's or PhD in Computer Science

Tools

DeepSpeed

FSDP

SLURM

K8s (Kubernetes)

CUDA

Job description

Mistral is seeking a Research Engineer - ML track in Paris to build and optimize large-scale learning systems. You will collaborate with Research Scientists to move ideas from research to production across platforms and embedded squads.

You'll implement robust ML tools, experiment with cutting-edge deep learning techniques, and write clear, efficient Python code. This role offers an opportunity to shape open-weight models powering enterprise AI solutions.