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Senior AI Training Data Snapshot Platform Engineer

Connor Leclerc

Full-time · Job · Los_Angeles

About the role

What we have: a model registry, a feature store, and experiment tracking that hundreds of ML teams rely on. What's missing: a reliable way to say exactly which data a model was trained on, months later, at petabyte scale. Customers in finance and healthcare are asking for it, auditors are asking for it, and our own reproducibility features break without it. Gravex Cloud is hiring a senior engineer to design immutable, cheap training data snapshots that plug into everything we already run. You'll choose the storage format, define the API, work out deduplication and retention, and lead two engineers through the build.

Responsibilities

  • Design the snapshot architecture: storage layout, metadata model, retention policies
  • Lead a team of two engineers from design doc to general availability
  • Integrate snapshots with our registry and experiment tracking so lineage is automatic
  • Own cost targets; snapshots must cost less than 5% of the underlying storage

Requirements

  • Extensive experience building large-scale data infrastructure (Spark, object storage, table formats)
  • Track record leading technical designs across multiple teams
  • Familiar with ML workflows and why reproducibility matters to practitioners
  • Experience with Iceberg, Delta or Hudi is highly relevant

Benefits

  • Remote in the US or Canada
  • Top-of-band salary plus equity refresh
  • Annual offsite
  • Comprehensive health coverage
  • $3,000 yearly learning budget

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Categories

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python spark airflow kubernetes aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python spark airflow kubernetes aws mlflow

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