Lead Applied Scientist, South Korea

• Lead the technical execution of high-stakes frontier science projects.

• Leading teams and strategic initiatives in the Applied Science team, defining team culture

• Be the point of contact internally and externally for technical Applied Science projects in the local region. This includes: leading the pre- and post-sales technical scoping, running events, engaging executive stakeholders, and ensuring projects align with the long-term vision of Applied Science at Mistral.

• Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.

• Work across a diverse set of complex real world problems such as robotics, engineering, finance, cybersecurity, physics and more.

• Generate and curate data for pre-training and post-training, working on evaluations and making sure the model's performance beats customer expectations and frontier benchmarks.

• Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
  

• You are fluent in English and Korean, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.

• You have experience leading a technical AI, science or engineering team. Balancing technical IC work with team leadership and stakeholder management.

• 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 and high autonomy.

• Low-ego, collaborative and eager to learn.

• Track record of success through personal projects, professional projects or academia.
  

Nice to have

• Ex-founder or builder

• Loves to build a dynamic, hard-working and exciting team culture

• 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.

• Experience working on large code bases or large machine learning models at scale.

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

• Publications in top academic journals or conferences.

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