Senior Research Engineer, Privacy and Anonymization
About the Role
Build privacy and anonymization systems that help make sensitive real-world data safe and useful for AI training. You will develop end-to-end methods to protect sensitive information while preserving the structure and signal needed for downstream training, evaluation, and synthetic data workflows.
What You'll Do
Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, and tailor transformations to data types and use cases.
Develop and benchmark detection approaches that combine rules, statistical models, classifiers, and LLM-based methods.
Create production pipelines that anonymize data before it enters processing, training, evaluation, or synthetic data workflows.
Develop evaluation frameworks for privacy risk and retained utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
Design robust systems that handle new sources, schema drift, unusual formats, and sensitive information in unexpected fields.
Partner with engineering, research, operations, and customers to turn privacy requirements into practical safeguards.
