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Mistral is seeking an Applied AI Engineer to drive customer adoption of its full-stack AI solutions—from frontier models to developer tools and applications. You'll work across high-stakes industries including finance, manufacturing, defense, healthcare, and the public sector, helping enterprises deploy customized AI systems.
In this role, you'll be the technical bridge between Mistral's research and production environments. You'll manage customer relationships across multiple stakeholders (executives, data scientists, engineers) from pre-sale through post-implementation. Key responsibilities include onboarding customers on Mistral's products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring seamless production integration with backend and frontend systems.
You'll work on state-of-the-art generative AI applications spanning consumer products to industrial use cases. You'll individually lead deployment of production systems with significant business impact, collaborate with researchers and product engineers on complex projects involving advanced fine-tuning and LLM applications, and contribute to open-source codebases for inference and fine-tuning tasks.
You'll participate in pre-sales calls to understand client needs and provide technical guidance on Mistral technologies to diverse stakeholders. Your feedback loop with the product and science teams will directly influence improvements to product and model capabilities.
Required qualifications: PhD or Master's in AI/Data Science; 2+ years as a technical individual contributor (data scientist or software engineer) on AI products; hands-on experience with LLM fine-tuning, advanced RAG, and agentic use cases; deep understanding of machine learning and LLM concepts; proven experience building and deploying LLM/NLP applications; strong Python coding skills; PyTorch experience; familiarity with agent frameworks (Langchain) and vector databases; excellent communication skills explaining complex concepts to technical and non-technical audiences; fluency in English and Korean.
Ideal candidates have contributed to open-source LLM projects or worked as Customer Engineers, Forward Deployed Engineers, Sales Engineers, Solutions Architects, or Technical Product Managers.
