Mistral AIApplied Scientist - Research Engineer (Formal Methods), EMEA
Mistral AI is hiring an Applied Scientist - Research Engineer (Formal Methods), EMEA in Paris, France. Level rates it ; you can apply on Mistral AI.
Level's read on this job
- Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
- Tools and skills the posting cites include PyTorch and JAX.
- Level lists 215 other open roles at Mistral AI.
- The role was posted in the last few days.
AI in this role
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.
How we rate this
Applied Scientist - Research Engineer (Formal Methods), EMEA at Mistral AI rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- Typical applied scientist job
- $167k
This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used JAX in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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