Applied Scientist/Research Engineer, EMEA

The Role

As an Applied Scientist/Research Engineer on the Mistral AI research team, you will drive key research efforts and partner with clients to solve challenging problems in artificial intelligence. Your work will focus on building and applying advanced models across text, image, and speech, aiming to deliver real, measurable impact. Collaborating closely with internal and external teams in science, engineering, and product, you will play a central role in developing AI solutions with tangible results.

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.

   

• 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 (Mathematics, Physics, Machine Learning) — exceptional candidates from other backgrounds welcome.

• Research experience in agents, multimodal models, world models, robotics, diffusion models, cybersecurity, 3D understanding/generation, or time-series analysis.

• Contributions to a large open-source or industry codebase.

• Publications in top academic journals or conferences.

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