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AI Model Quantization Accuracy Validator

Evan Ferrari

Full-time · Job · Los_Angeles

About the role

GPU spend and model accuracy are constantly in tension on our platform, and customers keep asking us to quantize aggressively without telling them exactly what they're trading away. This role builds the validation harness that measures accuracy degradation across quantization levels for customer models before deployment, then generates a report customers can use to make an informed cost-versus-quality decision instead of guessing.

Responsibilities

  • Build validation harnesses measuring accuracy loss across quantization levels
  • Generate customer-facing reports on cost-versus-accuracy tradeoffs
  • Track quantization regressions across mlflow experiment runs
  • Partner with platform team on default quantization recommendations

Requirements

  • Deep experience with pytorch and tensorflow model optimization
  • Familiarity with quantization techniques (int8, mixed precision, etc.)
  • Comfortable with mlflow for experiment tracking at scale
  • Experience with gcp-hosted training and inference infrastructure

Benefits

  • Fully remote position
  • Equity package
  • Health, dental, and vision insurance
  • Annual GPU hardware allowance for home lab experiments

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Categories

MLOps & AI Infrastructure

Skills

python pytorch tensorflow mlflow gcp

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python pytorch tensorflow mlflow gcp

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