About this offer
- Employer
- Clera
- Source
- getclera.com · careers site
- Posted
- 5 Nov 2026 · 3 days ago
- Work
- On site
- Place
- San Francisco, United States
- Sponsorship
- Stated in the job posting
Visa and relocation details are read automatically from the job posting. Always confirm them with the employer.
Visa sponsorship
Clera sponsors the work visa for this role.
- Work visa sponsored
- Confirm the details with the employer
Visa sponsorship is available.
The role
About the Role
Build privacy and anonymization systems for an AI infrastructure team, helping make sensitive real-world data safe and useful for model training. You will own production methods that protect private information while preserving the structure and signal needed for training and evaluation.
What You'll Do
Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information, and choose 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 raw data before downstream processing, training, evaluation, or synthetic data generation.
Build evaluation frameworks for privacy risk and retained utility, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
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.
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 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; experience with privacy-enhancing technologies or sensitive data in healthcare, finance, or security 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.