Applied Scientist

Mistral•Palo Alto, CA

11h

About The Position

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.

Requirements

Excellent communication skills. You are 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 and can find yourself around independently with little guidance.
Write clean, readable, high-performance, fault-tolerant Python code.
Low-ego, collaborative and eager to learn.
A track record of success through personal projects, professional projects or in academia.

Nice To Haves

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.

Responsibilities

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.