Research Engineer, Machine Learning
About the role
Full text from the employer, as published on Arbeitnow, arranged into sections. Nothing added or removed.
01About 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.
02About 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.
03What 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.
04What 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.
05What 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.
06Privacy Policy
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
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DGJ Insight
Our own data about this role and place, from official statistics and our live job index.
Source: OECD Average annual wages, 2025
UN living-cost index for Paris (ICSC post adjustment 50.5), as of 1 Oct 2026.
Source: ICSC post adjustment classifications (icsc.un.org)
- Talent Passport: Qualified employees, researchers, artists, investors; multi-year permit
- Employee (salarié) visa: Employer work authorisation from the labour office
- Temporary worker visa: Contracts under 12 months
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