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AI Dataset Provenance Verification Engineer

Noah Kovacs

Full-time · Job · London

About the role

Our clients include enterprises that need to prove, in writing, exactly which datasets trained the models they deploy — increasingly a hard requirement from their own regulators and auditors. The team you'd join already builds bias and fairness auditing tools; the piece we're missing is a way to verify and certify dataset provenance itself, tracing training data back to its original source and licensing terms. Our product blends automated lineage tracking with manual audit workflows, and we expect you to be comfortable working across both — writing the pipelines and helping define what 'verified' actually means for a client audit.

Responsibilities

  • Build pipelines that trace training datasets back to original sources
  • Design provenance verification checks integrated into audit workflows
  • Partner with the fairness and bias team on shared tooling
  • Document provenance findings in client-ready audit reports

Requirements

  • 5+ years in data engineering with strong SQL and Spark skills
  • Experience with data lineage or metadata tracking systems
  • Comfortable working in a compliance-heavy, audit-driven environment

Benefits

  • Fully remote with flexible hours
  • Top-of-market compensation for specialized provenance expertise
  • Dedicated budget for research and continuing education

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Categories

MLOps & AI Infrastructure

Skills

python sql airflow spark

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

MLOps & AI Infrastructure

Skills

python sql airflow spark

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