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AI Streaming Join Skew Detection Engineer

Benjamin Leclerc

Full-time · Job · UTC

About the role

Have you ever watched a streaming join silently fall over because one key had ten thousand times more events than every other key? We build the real-time data infrastructure that dozens of AI teams depend on, and skewed joins are the most common cause of pipeline outages we see. You'll build the detection layer that flags skew before it takes down a downstream model, then work with the platform team to auto-rebalance affected joins. We don't care where you work from. We care about output, clear communication, and ownership of the systems you build.

Responsibilities

  • Build skew detection for high-throughput streaming joins
  • Design auto-rebalancing logic for affected Kafka partitions
  • Investigate production incidents caused by join skew
  • Document runbooks for on-call engineers

Requirements

  • 3+ years working with Kafka and Spark streaming
  • Strong Python and SQL skills
  • Experience debugging distributed systems incidents
  • Comfortable working async across time zones

Benefits

  • Fully remote, async-friendly culture
  • Competitive salary plus equity
  • Home office stipend
  • Flexible working hours

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

spark kafka python sql

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$130k – $160k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

spark kafka python sql

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