Research Engineer, Privacy and Anonymization
About the Role
Build privacy and anonymization systems for an AI infrastructure team, helping make sensitive real-world data safer to use in model training and evaluation. You will develop end-to-end methods that protect sensitive information while preserving the structure and utility of data.
What You'll Do
Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, then choose transformations suited to the data and its downstream use.
Develop and benchmark detection approaches using rules, statistical models, classifiers, and LLM-based methods.
Build production pipelines that anonymize data before it enters processing, training, evaluation, or synthetic data workflows.
Create evaluation frameworks for privacy risk and retained utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
Design systems that handle new data sources, schema drift, unusual formats, and sensitive information in unexpected fields.
Collaborate across engineering, research, operations, and customer-facing teams to turn privacy requirements into practical safeguards.
