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AI Privacy-Preserving Data Generation Researcher

Savannah Watanabe

Full-time · Job · Los_Angeles

About the role

Differential privacy promises mathematical guarantees that synthetic data can't leak individual records. In practice, the privacy-utility trade-off is brutal: tighten the privacy budget and the synthetic data becomes useless for training; loosen it and the guarantees become meaningless. We're pushing the frontier of this trade-off for healthcare and financial services clients who need both strong privacy and high-fidelity synthetic data. Our research team publishes at top venues — NeurIPS, ICML, AISTATS — and every publication feeds directly into our product. You'll split time between advancing the theory (new mechanisms for tabular and sequential data, tighter privacy accounting, better utility metrics) and implementing production-grade generators that our clients deploy on-premise behind their firewalls. The team is three researchers and two engineers. You'll be the bridge: someone who can prove a theorem on Monday and ship a Docker container on Friday. We need both, and finding people who do both well is rare.

Responsibilities

  • Advance privacy-preserving data generation methods through original research
  • Implement production-grade synthetic data generators with differential privacy guarantees
  • Design privacy accounting frameworks for complex generation pipelines
  • Evaluate utility-privacy trade-offs across different data domains
  • Publish findings at top ML and privacy conferences
  • Support client deployments of on-premise synthetic data solutions

Requirements

  • 5+ years in ML research with publications in privacy, generative models, or statistics
  • Deep understanding of differential privacy theory and mechanisms
  • Strong PyTorch skills for implementing generative models
  • Experience with tabular or sequential data generation
  • PhD in ML, statistics, or related field preferred

Benefits

  • Fully remote with flexible schedule
  • Competitive research compensation
  • Unlimited conference travel budget
  • 20% time for independent research
  • Equity participation in a growing company

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch statistics docker aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch statistics docker aws

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