New - Applied AI Engineer

Mistral AI Mistral AI · AI Frontier · Paris, France · Solutions

Applied AI Engineer role focused on bridging Mistral's AI research with real-world enterprise applications. This customer-facing role involves deploying production-ready GenAI use cases, collaborating on fine-tuning and advanced LLM applications, and participating in pre-sales to understand client needs. The engineer will work with researchers, AI engineers, and product teams to deliver measurable business impact across diverse industries.

What you'd actually do

  1. Deploy production-ready AI use cases with significant business impact across diverse industries.
  2. Develop state-of-the-art GenAI applications, from consumer products to industrial solutions, driving technological transformation for customers.
  3. Collaborate with researchers, AI engineers, and product teams on complex customer projects involving fine-tuning, advanced LLM applications, and contributions to open-source codebases.
  4. Participate in pre-sales calls to understand client needs, challenges, and aspirations, providing technical guidance on Mistral’s products.
  5. Work with product and science teams to continuously improve model and product capabilities based on customer feedback.

Skills

Required

  • Fluency in English
  • Experience as a technical individual contributor (data scientist or software engineer) on AI-based products
  • Proven track record in implementing AI or machine learning products with APIs, back-end, and front-end interfaces
  • Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases
  • Deep understanding of machine learning and LLM concepts and algorithms
  • Strong technical coding skills in Python
  • Ability to explain complex technical concepts clearly to both technical and non-technical audiences
  • Contributions to open-source projects, particularly in the LLM space

What the JD emphasized

  • Proven track record in implementing AI or machine learning products with APIs, back-end, and front-end interfaces.
  • Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases.
  • Deep understanding of machine learning and LLM concepts and algorithms.
  • Strong technical coding skills in Python.

Other signals

  • customer-facing technical organization
  • deploy AI solutions that deliver measurable business impact
  • customer projects involving fine-tuning, advanced LLM applications