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Research Engineer, Privacy and Anonymization

HUD· Engineering & Research
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San Francisco, Singapore, Remote (Asia), Remote (North America)$100k - $230kFull-timePosted 1mo ago

About the role

Role focused on building privacy and anonymization systems to detect and remove sensitive information from data before it enters processing pipelines, preserving data utility for AI training.

Responsibilities

  • Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information and design transformations based on the data type and downstream use case
  • Develop and benchmark detection approaches that combine rules, statistical models, classifiers, and LLM-based methods
  • Build production pipelines that anonymize raw data before it enters downstream processing, training, evaluation, or synthetic data generation workflows
  • Create evaluation frameworks that measure privacy risk and retained data utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts
  • Design systems that remain robust to new data sources, schema drift, unusual formats, and sensitive information embedded in unexpected fields
  • Work with engineering, research, operations, and customers to translate privacy requirements into practical technical policies and safeguards

Qualifications

  • Strong proficiency in Python and experience building reliable production data or ML systems
  • Experience with information extraction, named-entity recognition, classification, or related methods for detecting rare or sensitive content
  • Strong experimental instincts and the ability to compare approaches across recall, precision, latency, cost, and downstream data utility
  • An understanding of the difference between redaction, masking, pseudonymization, anonymization, and synthetic data—and when each is appropriate
  • High attention to detail and the ability to reason about subtle leakage paths, edge cases, and adversarial failure modes
  • Built data processing pipelines end-to-end without a fully prescribed roadmap

Skills

Required:PythonInformation extraction / NER / classification

Benefits

  • Competitive compensation
  • 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees)
  • Lunch and dinner for in-office employees
  • Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays
  • 401k with a 4% match
  • Other perks including an Equinox membership and commuter benefits (US employees) and a health/wellness stipend (Singapore employees)
  • Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
  • Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place
  • Annual travel budget to visit either office
Last updated Oct 25, 2026. Interested? Apply on the company site.

About HUD

The platform for building RL environments

The platform for building RL environments. Train specialized agents, evaluate models, and deliver frontier‑grade post‑training data to labs.

AI benchmarkingEnvironment SDKGRPO trainingHUD Vendor PlatformMCP environmentsRL environmentsTraining + Eval Platformagent training
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