Applied Ai, Forward Deployed Machine Learning Engineer- Singapore

Mistral AI Mistral AI · AI Frontier · Singapore · Solutions

Applied AI Engineer at Mistral AI focused on customer adoption of AI products, including onboarding, guidance on prompting, evaluation, fine-tuning, and ensuring production integration. Works on GenAI applications, deploys use cases with business impact, collaborates with researchers and engineers on complex customer projects, and participates in pre-sales calls. Requires experience in fine-tuning LLMs, RAG, agentic use cases, and deploying LLM/NLP applications.

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

  • Fluent in English
  • 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

  • production integration
  • state-of-the-art GenAI applications
  • deploy into production use cases
  • complex fine-tuning
  • state-of-the-art LLM applications
  • fine-tuning
  • inference
  • building and deploying LLMs or NLP applications
  • AI or machine learning product implementation

Other signals

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