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AI Training-Serving Skew Detection Engineer

Aubrey Okafor

Full-time · Job · Chicago

About the role

Our mission is to make sure the features a model sees in production match what it saw during training, because that mismatch quietly ruins more models than any algorithm choice ever does. You'll be the third feature platform engineer on a team of eight, working directly with the ML platform lead to build skew detection into our feature pipeline by default rather than as something teams bolt on after a model mysteriously degrades. Velmox Data already handles feature engineering, drift monitoring, and data quality SLAs — training-serving skew detection is the missing piece that ties those together, and you'll own it end to end, splitting time between remote work and two days a week with the platform team.

Responsibilities

  • Build training-serving skew detection into the default feature pipeline
  • Design alerting for detected skew before it degrades production model quality
  • Integrate skew detection with existing drift monitoring and quality SLA systems
  • Partner with the ML platform lead on rollout across feature pipelines
  • Document skew detection methodology for other feature platform teams

Requirements

  • Strong Spark experience with large-scale feature pipelines
  • MLflow or equivalent experiment tracking experience
  • AWS production experience
  • Experience with training-serving skew or data drift problems
  • Willingness to work on-site two days a week

Benefits

  • Hybrid schedule, two days on-site
  • Equity package
  • Health, dental, and vision insurance
  • 401k matching
  • Annual ML platform conference budget

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

python spark aws mlflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python spark aws mlflow

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