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Mistral is a full-stack AI company providing frontier models, developer tools, applications, and compute infrastructure. They partner with enterprises across finance, manufacturing, defense, healthcare, and the public sector to co-create customized AI systems.
As an Applied Scientist, you will drive innovative research and collaborate with clients on complex AI projects. Your responsibilities include developing state-of-the-art models across multiple modalities (text, image, speech) and applying these models to diverse use cases and domains.
Key responsibilities:
- Run pre-training, post-training, and deploy models on large-scale GPU clusters (thousands of GPUs), handling distributed training challenges like OOM errors and NCCL communication issues
- Generate, curate, and evaluate data for pre-training and post-training pipelines, ensuring model performance meets or exceeds expectations
- Develop tools and frameworks to facilitate data generation, model training, evaluation, and deployment
- Collaborate cross-functionally with science, engineering, and product teams to build complex AI solutions using agents and RAG pipelines
- Manage research projects and maintain communications with client research teams
Required qualifications:
- Fluency in English and Korean with excellent communication skills; ability to explain complex technical concepts to diverse audiences
- Expert-level proficiency in PyTorch or JAX
- Ability to contribute independently to large codebases with minimal guidance
- Strong Python skills with emphasis on clean, readable, high-performance, fault-tolerant code
- Self-directed approach to shipping work without requiring roadmaps or micromanagement
- Track record of success through personal projects, professional work, or academic research
- Low-ego, collaborative mindset with eagerness to learn
Preferred qualifications:
- PhD or Master's degree in Mathematics, Physics, Machine Learning, or related field (exceptions made for exceptional candidates)
- Diverse research experience in areas such as agents, multi-modality, robotics, diffusion models, or time-series
- Contributions to large-scale codebases (open source or industry)
- Publications in top-tier academic journals or conferences
- Passion for code quality improvements including typing, testing, and CI/CD pipelines
