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AI Feature Store Developer

Connor Leclerc

Full-time · Job · Berlin

About the role

Feature engineering is where data scientists spend 60% of their time, and most of that time is wasted rebuilding features someone else already created. Our feature store solves this: a centralized registry where teams define, share, and serve ML features with consistent logic across training and inference. We launched the feature store internally eight months ago, and 14 data science teams now use it. Your job is to keep it running and make it better. That means fixing bugs, adding new data source connectors, improving the query performance, and building the monitoring that tells us when feature pipelines are late or producing unexpected values. You'll be the second junior engineer on a platform team of four. The senior engineers handle architecture and complex performance problems; you'll handle the steady flow of integration work, bug fixes, and user-reported issues. It's a hands-on role where you'll learn MLOps by building real infrastructure that data scientists depend on every day.

Responsibilities

  • Maintain and improve the internal feature store platform
  • Build connectors for new data sources as teams request them
  • Implement feature monitoring and data quality checks
  • Fix bugs reported by data science teams and prioritize based on impact
  • Write and update technical documentation for feature store users
  • Participate in on-call rotation during business hours

Requirements

  • 1+ year of Python development with SQL proficiency
  • Basic understanding of data pipelines and ETL concepts
  • Familiarity with cloud services like AWS or GCP
  • Interest in MLOps and data infrastructure
  • Ability to debug issues systematically and communicate fixes clearly

Benefits

  • Fully remote across EU time zones
  • 28 days PTO
  • €1,500 learning budget
  • Structured mentorship from senior engineers
  • Regular salary reviews every 6 months

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

python sql spark aws docker

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python sql spark aws docker airflow

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