Applied Ai, Forward Deployed Machine Learning Engineer - Palo Alto

Mistral AI Mistral AI · AI Frontier · Palo Alto, CA · Solutions

Applied AI Engineer at Mistral AI focused on customer adoption of AI products and APIs. Responsibilities include onboarding, guidance on prompting, evaluation, fine-tuning, production integration, and deploying GenAI applications. Collaborates with researchers and engineers on complex customer projects, including fine-tuning and LLM applications. Involved in pre-sales to understand client needs and provide technical guidance. Contributes to open-source codebases for inference and fine-tuning. Works with state-of-the-art GenAI applications and deploys them into production with significant business impact.

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

  • 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 adoption
  • production integration
  • state-of-the-art GenAI applications
  • deploy into production
  • complex fine-tuning
  • state-of-the-art LLM applications
  • open source codebases
  • pre-sales calls
  • technical guidance
  • improve continuously our product and model capabilities based on customers’ feedback
  • Fine Tuning LLMs
  • advanced RAG
  • agentic use cases
  • building and deploying LLMs or NLP applications
  • AI or machine learning product implementation with APIs, back-end and front-end interfaces
  • deep learning with Pytorch
  • agents framework such as Langchain
  • vector DBs

Other signals

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