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 to drive innovative research and collaborate with clients on complex research projects.
You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle.
• Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.
• Generate and curate data for pre-training and post-training, working on evaluations and making sure the model’s performance beats expectations.
• 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 using agents and RAG pipelines.
• Manage research projects and communications with client research teams.
• You have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.
• You’re an expert with PyTorch or JAX.
• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.
• You write clean, readable, high-performance, fault-tolerant Python code.
• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.
• Low-ego, collaborative and eager to learn.
• You have a track record of success through personal projects, professional projects or in academia.
• Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning, Computer Science & Engineering), but if you’re an exceptional candidate from a different background, you should apply.
• Can bring a variety of research experience (agents, multi-modality, robotics, diffusion, time-series).
• Have contributed to a large codebase used by many (open source or in the industry).
• Have a track record of publications in top academic journals or conferences.
• Love improving existing code by fixing typing issues, adding tests and improving 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.
Design, train, and deploy models that understand and reason over tabular data, while building datasets, evaluation tools, and benchmarks for structured-data use cases.
Conduct environmental and natural resource assessments by analyzing large datasets, evaluating contamination and restoration options, and preparing technical reports and plans using scientific, statistical, GIS, and database methods.
Research and deploy ultra-low-latency trading strategies by analyzing market data, developing exchange simulators and alpha signals, and measuring strategy performance and market competitiveness.
Research and develop large language models by designing experiments, curating data, optimizing transformer architectures, and training models on distributed infrastructure for production deployment.
Develop and validate radar-based precipitation algorithms and products using dual-polarization data, while analyzing radar variables, troubleshooting data quality issues, and collaborating on new platform capabilities.
