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Paris, Ile-de-France, France
Actively hiring, first seen by us todayWork setup in the employer’s posting: HybridFrom the employer’s posting
Employment type in the employer’s posting: FullTimeFrom the employer’s posting
You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases.
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.
The Role Mistral AI is seeking Applied Scientists and Research Engineers focused on tabular data. You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry.
Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data. 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.
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.
Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN).
Experience with text-to-SQL, table question answering, or spreadsheet agents.
Experience with reinforcement learning using verifiable rewards (e.g. query execution).
Experience working on large code bases or large machine learning models at scale.
- Ex-founder or builder - PhD / Master in a relevant field (Computer Science, Statistics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with text-to-SQL, table question answering, or spreadsheet agents.
From the employer’s posting.
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute.
In the employer’s words · Read in context
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 7 and day 57.
From 10,789 similar postings that came down. Coming down is not always a hire.
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- 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.
- Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
- Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN). - Strong background in machine learning on tabular data, including classical baselines (e.g. gradient boosting), and comfortable with SQL, pandas, and messy real-world data. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance.
- PhD / Master in a relevant field (Computer Science, Statistics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with text-to-SQL, table question answering, or spreadsheet agents. - Experience with reinforcement learning using verifiable rewards (e.g. query execution).
- 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. - Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN).
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New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
Mistral AI is seeking Applied Scientists and Research Engineers focused on tabular data. You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases.
Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry.
Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.
Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data.
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.
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.
Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN).
Strong background in machine learning on tabular data, including classical baselines (e.g. gradient boosting), and comfortable with SQL, pandas, and messy real-world data.
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.
Ex-founder or builder
PhD / Master in a relevant field (Computer Science, Statistics, Machine Learning) — exceptional candidates from other backgrounds welcome.
Experience with text-to-SQL, table question answering, or spreadsheet agents.
Experience with reinforcement learning using verifiable rewards (e.g. query execution).
Experience working on large code bases or large machine learning models at scale.
Contributions to a large open-source or industry codebase.
Publications in top academic journals or conferences.
Enjoys improving existing code: typing, tests, CI pipelines.
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.
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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Paris, Ile-de-France, France
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