Clera
Research Engineer, Privacy and Anonymization
- Location
- San Francisco, CA, US
- Arrangement
- On-site
- Employment type
- Full-time
- Posted
- 1 October 2026 (today)
Checked todayApplications go to the employer, never to RoleSprint
About this role
ABOUT THE ROLE
This Research Engineer role sits at the intersection of privacy engineering and AI infrastructure, owning the systems that make sensitive, real-world data safe for AI training. You will design and build end-to-end anonymization pipelines that protect privacy without sacrificing the structure and signal that make data valuable for training frontier AI agents. The work is high-impact: it directly gates what data can enter production training, evaluation, and synthetic data workflows.
WHAT YOU'LL DO
- Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, designing transformations based on data type and downstream use case.
- Develop and benchmark detection approaches that combine rules, statistical models, classifiers, and LLM-based methods.
- Build production pipelines that anonymize raw data before it enters downstream processing, training, evaluation, or synthetic data generation workflows.
- Create evaluation frameworks that measure privacy risk and retained data utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
- Design systems that remain robust to new data sources, schema drift, unusual formats, and sensitive information embedded in unexpected fields.
- Collaborate with engineering, research, operations, and customers to translate privacy requirements into practical technical policies and safeguards.
WHAT WE'RE LOOKING FOR
- 2+ years of hands-on experience building production data or ML systems in Python.
- Proficiency in Python with a track record of building reliable, production-grade systems.
- Hands-on experience with PII detection, removal, or anonymization.
- Experience with information extraction, named-entity recognition, classification, or related methods for detecting sensitive or rare content.
- Proven ability to build end-to-end data processing pipelines without a fully prescribed roadmap.
- Strong experimental instincts: comfortable comparing approaches across recall, precision, latency, cost, and downstream data utility.
- Solid understanding of privacy transformation techniques: redaction, masking, pseudonymization, anonymization, and synthetic data generation.
- Experience designing systems that are robust to schema drift, unusual data formats, and edge cases.
- Familiarity with privacy-enhancing technologies such as differential privacy, k-anonymity, secure aggregation, or format-preserving encryption is a plus.
- Experience with low-latency or high-throughput ML inference and data-processing systems is a plus.
- Prior work with sensitive data in healthcare, finance, or security domains is a plus.
LOCATION
On-site in San Francisco, California, USA. Visa sponsorship is available.
Work location
- San Francisco, CA, US
Related jobs
Ready to make a decision?
This role is either worth your time or it isn’t.
Analyze the posting against your experience, see the gaps clearly, and build the right materials only if the opportunity makes sense.
Nothing is submitted automatically. You choose what happens next.
About this listing
Published on Ashby under the board identifier Clera, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 1 October 2026, last checked today. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.