# Research Engineer, Privacy and Anonymization at Clera

Research Engineer, Privacy and Anonymization at Clera in San Francisco. On-site, full-time, paying $130k–$225k. Posted October 28, 2026.

- Company: Clera
- Location: San Francisco
- Workplace: On-site
- Job type: Full-time
- Pay: $130k–$225k
- Experience: 2+ years
- Posted: 2026-10-28
- Apply: https://jobs.ashbyhq.com/clera/1c704f5b-f92a-4856-947f-fc087d6de9a8/application
- Source: https://jobmagic.ai/jobs/research-engineer-privacy-and-anonymization-clera-9tsce4

## Requirements

- 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.

## Description

### 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.