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Clera

Research Engineer, Privacy and Anonymization (Mid-Level)

San Francisco
Salary
$130,000 - $225,000
Level
Mid
Work type
On-site · San Francisco
Visa
Sponsors visas

Open. First seen 13 October 2026.

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The team: Engineering HIRES STEADILY

This role is one of 246 open in Engineering. 180 were posted in the last 30 days and the oldest in March: a team that hires all year rather than one being built.

WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS

LLM (118 of 246), TypeScript (112 of 246), Python (103 of 246), React (92 of 246), Machine Learning (61 of 246), PostgreSQL (44 of 246), JavaScript (41 of 246)

OTHER ROLES ON THIS TEAM

From the team and dates on Clera's own job board.

About the role

About the Role

Build privacy and anonymization systems that make sensitive real-world data safer to use in AI training and evaluation. You will develop detection and transformation methods, then bring them into production pipelines while preserving useful data structure and signal.

What You'll Do

  • Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, and apply transformations suited to each data type and use case.
  • Develop and benchmark detection methods using rules, statistical models, classifiers, and LLM-based approaches.
  • Create production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic data generation.
  • Measure privacy risk and retained data utility with evaluation frameworks, 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.
  • Partner with engineering, research, operations, and customers to turn privacy requirements into practical technical safeguards.

What We're Looking For

  • At least 2 years of experience building production data or ML systems in Python.
  • Hands-on experience detecting, removing, or transforming PII while preserving useful data characteristics.
  • Experience with information extraction, named-entity recognition, classification, or related methods 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.
  • Experience handling schema drift, unusual formats, and edge cases; familiarity with privacy technologies such as differential privacy, k-anonymity, secure aggregation, or format-preserving encryption is valuable.
  • Experience with sensitive data in healthcare, finance, security, or related fields, and with low-latency or high-throughput ML systems, is beneficial.

Compensation & Benefits

Annual salary range: $130,000 to $225,000. Visa sponsorship is available.

Location

On-site in San Francisco, California, United States.

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