Applied Scientist - Research Engineer (Formal Methods), EMEA

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.

The Role

Mistral AI is seeking Applied Scientists and Research Engineers focused on formal methods. You will design, train, and deploy SOTA large language models and apply them to diverse use cases.

You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions.

What You Will Do

Run pre-training, post-training and deploy state of the art models on large clusters.

Generate and curate datasets for theorem proving and software verification, and build evaluators and benchmarks for formal reasoning.

Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.

Collaborate with cross-functional teams to tackle complex use cases.

Manage research projects and communications with client research teams.

What We're Looking For

Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences.

Expert with PyTorch or JAX.

Not afraid of contributing to a big codebase; finds their way around independently with little guidance.

Writes clean, readable, high-performance, fault-tolerant Python code.

Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence.

Low-ego, collaborative and eager to learn.

Track record of success through personal projects, professional projects or academia.

Nice to have

PhD / Master in a relevant field (Computer Science, Mathematics, Machine Learning).

Experience with autoformalization, proof automation, or verified code generation.

Experience with reinforcement learning using verifiable rewards, ideally from Lean or other proof assistants.

Contributions to a large open-source or industry codebase.

Publications in top academic journals or conferences.

Enjoys improving existing code: typing, tests, CI pipelines.

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 .

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .