Applied Scientist / Research Engineer, EMEA — AI Pioneer

Mistral; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Healthcare coverage

Parental leave

Retirement plans

Relocation support

Wellness programs

Meal and transportation allowances

Résumé du poste

Mistral AI is seeking an Applied Scientist/Research Engineer to drive key research and partner with clients to solve challenging AI problems. You will build and apply state-of-the-art models across text, image and speech to deliver real, measurable impact.

Collaboration with science, engineering and product teams is essential as you run pre-training, post-training and deployment on clusters with thousands of GPUs, and develop tools to enable data generation, training and evaluation.

Qualifications

• Fluent in English with excellent communication skills.
• Expert with PyTorch or JAX.
• Writes clean, readable Python code.
• Ability to navigate large codebases independently.
• Collaborative and eager to learn.
• Track record through personal projects, professional projects or academia.

Responsabilités

• 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, evaluating and beating performance.
• Develop 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.

Connaissances

PyTorch

JAX

Python

English communication

Independent worker

Open-source contribution

Description du poste

Mistral AI is seeking an Applied Scientist/Research Engineer to drive key research and partner with clients to solve challenging AI problems. You will build and apply state-of-the-art models across text, image and speech to deliver real, measurable impact.

Collaboration with science, engineering and product teams is essential as you run pre-training, post-training and deployment on clusters with thousands of GPUs, and develop tools to enable data generation, training and evaluation.