Research Engineer (ML) — Scale AI Pipelines & Production

Mistral; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Mistral is seeking a Research Engineer – ML track to build and optimise large-scale learning systems powering open-weight models. You will work closely with Research Scientists and join either Platform RE or Embedded RE teams to turn ideas into robust code.

Required: advanced degree in CS, 4+ years in large ML codebases, and hands-on with PyTorch, JAX or TensorFlow, plus distributed training tools. You thrive with collaboration and rigorous software practices.

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; distributed training (DeepSpeed / FSDP / SLURM / K8s).
• Experience in Deep learning, NLP or LLMs; CUDA or data-pipeline chops a bonus.

Responsibilities

• Accelerate researchers by taking on 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; run thousands of GPUs where needed.
• Design, implement and benchmark ML algorithms; write clear, efficient Python code.
• Deliver prototypes that become production-grade components for Le Chat and our enterprise API.

Skills

ML codebases

Distributed training

PyTorch

JAX

TensorFlow

CI/CD

NLP/LLMs

CUDA

Data pipelines

Code review

Education

Master’s or PhD in Computer Science

Tools

DeepSpeed

FSDP

SLURM

K8s

Job description

Mistral is seeking a Research Engineer – ML track to build and optimise large-scale learning systems powering open-weight models. You will work closely with Research Scientists and join either Platform RE or Embedded RE teams to turn ideas into robust code.

Required: advanced degree in CS, 4+ years in large ML codebases, and hands-on with PyTorch, JAX or TensorFlow, plus distributed training tools. You thrive with collaboration and rigorous software practices.