Applied Ai, Forward Deployed Machine Learning Engineer - Montreal

Mistral AI Mistral AI · AI Frontier · Montreal, QC · Solutions

Applied AI Engineer at Mistral AI focused on customer adoption of AI products, including onboarding, guidance on prompting, evaluation, fine-tuning, and production integration. The role involves working on GenAI applications, deploying use cases with business impact, collaborating with researchers and engineers on complex customer projects, and contributing to open-source codebases for inference and fine-tuning. Responsibilities also include pre-sales technical guidance 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

  • English fluency
  • PhD / master in AI / data science
  • 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
  • Fine Tuning LLMs
  • advanced RAG
  • 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
  • deep learning with Pytorch
  • agents framework such as Langchain
  • 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

  • experience in Fine Tuning LLMs
  • advanced RAG
  • agentic use cases
  • building and deploying LLMs
  • APIs, back-end and front-end interfaces
  • agents framework such as Langchain
  • vector DBs

Other signals

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