Research Engineer, Privacy and Anonymization
About the Role
This Research Engineer role sits at the intersection of privacy engineering and AI data infrastructure. You will own the full pipeline for detecting and removing sensitive information from raw, real-world data before it flows into processing, training, evaluation, and synthetic data workflows. The work is foundational: protecting privacy without destroying the structure and signal that make data valuable for training frontier AI agents.
What You'll Do
Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, and design appropriate transformations based on 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 f
