Research Engineer, Privacy and Anonymization

2 days ago

H1B sponsor

Base Salary

$130k - $225k/yr

Responsibilities

Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information.
Develop and benchmark rules, statistical models, classifiers, and LLM-based detection methods.
Create production pipelines that anonymize raw data before processing, training, evaluation, or synthetic data generation.
Build evaluation frameworks using privacy-risk metrics, leakage tests, and adversarial re-identification attempts.
Design robust systems for schema drift, unusual formats, and sensitive information in unexpected fields.
Partner with engineering, research, operations, and customers to translate privacy requirements into safeguards.

At least 2 years of experience building production data or ML systems in Python.
Hands-on experience detecting, removing, or anonymizing PII while preserving useful data characteristics.
Experience with information extraction, named-entity recognition, classification, or related sensitive-content detection techniques.
Experience building end-to-end data-processing pipelines and benchmarking recall, precision, latency, cost, and data utility.
Understanding of redaction, masking, pseudonymization, anonymization, and synthetic data generation.
Strong experimental skills and experience handling schema drift, unusual formats, and edge cases.
Technical education or equivalent background.
Experience with privacy-enhancing technologies or sensitive data in healthcare, finance, or security is valuable.