hirq
← All jobs

Clera

Research Engineer, Privacy and Anonymization

San Francisco · On-site · FullTime · Engineering

$130K – $225K

Apply well, not just fast

Create a free account and upload your resume to get a match score, keyword gaps, a tailored resume, a cover letter and interview prep for this job.

About the role

Machine LearningPythonLLMs
ABOUT THE ROLE Join a team building privacy and anonymization systems for sensitive real-world data used in AI training. You will develop methods that protect personal and confidential information while preserving the structure and signal that make data useful. WHAT YOU'LL DO - Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, then select transformations suited to each data type and use case. - Develop and benchmark detection methods combining rules, statistical models, classifiers, and LLM-based approaches. - Create production pipelines that anonymize data before downstream processing, training, evaluation, or synthetic data generation. - Build evaluation frameworks for privacy risk and retained data utility, including leakage tests and adversarial re-identification attempts. - Design robust systems that handle new data sources, schema drift, unusual formats, and sensitive information in unexpected fields. - Work with engineering, research, operations, and customers to turn privacy requirements into practical safeguards. WHAT WE'RE LOOKING FOR - At least 2 years of experience building production data or ML systems in Python, with hands-on experience transforming PII while preserving useful data characteristics. - Experience with PII detection, removal, or anonymization, and with information extraction, named-entity recognition, classification, or related techniques. - 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. - Experience with privacy-enhancing technologies such as differential privacy, k-anonymity, secure aggregation, or format-preserving encryption. - Strong experimental judgment and attention to edge cases; experience with sensitive data or high-throughput ML and data systems is valuable. COMPENSATION & BENEFITS Base salary: $130,000 to $225,000 annually. Visa sponsorship is available. LOCATION On-site in San Francisco, California, United States.