Research Engineer, Machine Learning

Mistral

Paris +3 more

Who this role is best for

Best suited to candidates with experience in large-scale ML codebases and a background in deep learning or NLP, working in high-stakes industries with a collaborative team structure across multiple European locations.

Best fit for

Candidates with experience in distributed training and deep learning frameworks like PyTorch or TensorFlow
— “Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training”
Individuals who have worked on large-scale ML systems and can bridge research and production
— “Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs”
Professionals with a proven track record in AI research and strong software design instincts
— “Master’s or PhD in Computer Science (or equivalent proven track record)”

Things to consider

This role demands a strong ability to work with distributed training systems and cluster tooling
— “comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s)”
The position involves working closely with research scientists in a dynamic, team-oriented environment
— “We are a dynamic, collaborative team passionate about AI and its potential to transform society”

How to stand out

Highlight experience in building robust tools for large-scale ML pipelines
— “Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools”
Emphasize your ability to turn research ideas into scalable code
— “turn fresh ideas into repeatable, scalable code”
Demonstrate your software design skills with examples of testing, code review, and CI/CD practices
— “Strong software-design instincts: testing, code review, CI/CD”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

accelerate researchers by taking on the heavy parts of large-scale ML pipelines
integrate checkpoints, streamline evaluation, and expose APIs
deliver prototypes that become production-grade components

Typical background

Master’s or PhD in Computer Science4 + years working on large-scale ML codebases

Skills & requirements

Required

Large-scale ML PipelinesDistributed TrainingPythonPyTorchJAXTensorFlowSoftware-design Instincts

Preferred

CUDAData-pipeline

Stack & domain

PythonPyTorchJAXTensorFlowDistributed TrainingCUDAData PipelinesDeepspeedFSDPSlurmKubernetesSelf-starterLow-egoCollaborativeAIMachine LearningDeep LearningNLPLlms

About the role

Original posting from Mistral via Ashby

ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
ABOUT THE RESEARCH ENGINEERING TEAM
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, Safety …) 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.
Design, implement and benchmark ML algorithms; write clear, efficient code in Python.
Deliver prototypes that become production-grade components for Vibe and our enterprise API.
What We're Looking For
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
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Source: Mistral careers (Ashby)