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AI Forward Deployed Engineer (GenAI) - Paris

Databricks · Paris

Nouveau
Senior 🇬🇧 English
HuggingFace LangChain DSPy PyTorch scikit-learn pandas AWS Azure GCP Apache Spark Databricks Intelligence Platform

Description du poste

About the role

Databricks' AI Forward Deployed Engineering (AI FDE) team is a specialist, customer-facing AI team that helps customers build and productionize first-of-its-kind AI applications. It works cross-functionally with engineering, product and developer relations, and supports internal subject matter expert teams. The role reports to the Senior Manager - AI FDE, EMEA. Candidates must be based in France; remote applicants living near the office are welcome, with Paris preferred.

Key responsibilities

  • Develop cutting-edge GenAI solutions using the latest techniques from Databricks AI research to solve customer problems
  • Own the production rollouts of consumer and internally facing GenAI applications
  • Serve as a trusted technical advisor to customers across a variety of domains
  • Present at conferences such as Data + AI Summit and act as a thought leader internally and externally
  • Work with product and engineering teams to influence priorities and shape the product roadmap

Required profile

  • Minimum 4 years of experience
  • Hands-on industry data science experience with common ML and data science tools
  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • Experience communicating and teaching technical concepts to both non-technical and technical audiences
  • Willingness to travel once every 4-8 weeks to see customers

Required skills

  • Building GenAI applications such as RAG, multi-agent systems, Text2SQL and fine-tuning with HuggingFace, LangChain and DSPy
  • Deploying production-grade GenAI applications, including evaluation and optimisation
  • Production-grade ML deployments on AWS, Azure or GCP
  • Preferred: Databricks Intelligence Platform and Apache Spark for large-scale distributed datasets

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Databricks

Paris