Research Engineer, Privacy and Anonymization

About the Role

This Research Engineer role sits at the intersection of privacy engineering and AI infrastructure, owning the systems that make sensitive, real-world data safe for AI training. You will design and build end-to-end anonymization pipelines that protect privacy without sacrificing the structure and signal that make data valuable for training frontier AI agents. The work is high-impact: it directly gates what data can enter production training, evaluation, and synthetic data workflows.

What You'll Do

• Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, designing 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 inf