Applied AI Engineer

Mistral AI Mistral AI · AI Frontier · Seoul, South Korea · Solutions

Applied AI Engineer at Mistral AI focused on customer adoption, deployment, and technical challenges. Responsibilities include onboarding customers, guiding on prompting/evaluation/fine-tuning, integrating solutions, working on GenAI applications, deploying use cases, collaborating with researchers and engineers on complex projects (fine-tuning, LLM applications, open-source codebases), participating in pre-sales calls, and providing technical guidance. Requires strong Python and PyTorch skills, experience with LLMs, NLP applications, APIs, back-end/front-end interfaces, agent frameworks (Langchain), and vector databases.

What you'd actually do

  1. You’ll be responsible for onboarding customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces.
  2. You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
  3. You’ll individually help deploy into production use cases with a considerable business impact across various industries.
  4. You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning.
  5. You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.

Skills

Required

  • English and Korean fluency
  • PhD / master in AI / data science
  • 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
  • Experience in Fine Tuning LLMs
  • tackling advanced RAG or agentic use cases
  • deep understanding of concepts and algorithms underlying machine learning and LLMs
  • building and deploying LLMs or NLP applications
  • AI or machine learning product implementation with APIs, back-end and front-end interfaces
  • strong technical coding skills in Python
  • experience with deep learning with Pytorch
  • experience with agents framework such as Langchain
  • experience with vector DBs
  • strong communication skills

Nice to have

  • Contributed to open-source projects in particular in the space of LLMs
  • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager

What the JD emphasized

  • complex fine-tuning
  • state-of-the-art LLM applications
  • fine-tuning
  • agentic use cases

Other signals

  • customer-facing role
  • deploying LLMs into production
  • fine-tuning
  • RAG
  • agentic use cases