Applied Ai, Forward Deployed Machine Learning Engineer

Mistral AI Mistral AI · AI Frontier · Montréal · Solutions

Applied AI Engineer at Mistral AI responsible for onboarding customers, guiding them on product usage, and collaborating on complex GenAI applications. This role involves deploying state-of-the-art LLM applications, fine-tuning, RAG, and agentic use cases into production, working closely with researchers and product engineers, and contributing to open-source codebases. The role also includes pre-sales support and gathering customer feedback for product improvement.

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 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

  • Fluent in English and French
  • 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
  • Experienced with building and deploying LLMs or NLP applications
  • Proven experience in 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, vector DBs
  • Strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences

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

  • customer-facing
  • production integration
  • production use cases
  • complex fine-tuning
  • state-of-the-art LLM applications
  • open source codebases
  • pre-sales calls
  • technical guidance
  • customer feedback

Other signals

  • customer-facing
  • production deployment
  • LLM applications
  • fine-tuning
  • RAG
  • agents