Research Engineer, Privacy and Anonymization

The role

Build privacy and anonymization systems for an AI infrastructure team. You will own production methods that protect private information while preserving the structure and signal needed for training and evaluation.

What you will do

• Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information
• Develop and benchmark detection methods combining rules, statistical models, classifiers, and LLM-based approaches
• Create production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic data generation
• Build evaluation frameworks for privacy risk and retained utility
• Design robust systems for new data sources, schema drift, unusual formats, and sensitive information in unexpected fields
• Partner with engineering, research, operations, and customers to turn privacy requirements into practical policies and safeguards

Required qualifications

• 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 techniques for detecting sensitive or rare content
• Experience building end-to-end data processing pipelines and benchmarking approaches across 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

Nice to have

• experience with privacy-enhancing technologies or sensitive data in healthcare, finance, or security is valuable

Before you apply

• Visa sponsorship is available

About the company

clera