Applied Scientist (Internship)

About 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 Scientist Interns and Research Engineer Interns 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. What You Will Do Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. 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 retrieval pipelines. 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 Pursuing a PhD / Master in a relevant field (Mathematics, Physics, Machine Learning) — exceptional candidates from other backgrounds welcome.