Description
HUD is hiring a Research Engineer to build privacy and anonymization systems for sensitive real-world data used in AI training and evaluation. The role develops methods to detect PII, credentials, secrets, and other sensitive information; combines rules, statistical models, classifiers, and LLM-based approaches; builds production anonymization pipelines; and creates evaluation frameworks for privacy risk and data utility. The position is full-time, based in San Francisco or Singapore, with remote work available for candidates who can overlap 70–80% with those time zones, and visa support is provided for strong candidates.
