- San Francisco, California, United States
- On-site
- Full-time · Associate
- $130K–$225K per year
- 2+ years
- Visa sponsorship
Build privacy and anonymization systems for an AI infrastructure team, helping make sensitive real-world data safe and useful for model training.
Compensation
Base salary: $130,000 to $225,000 annually.
Responsibilities
- 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.
Requirements
- Technical education or equivalent background
- Nice to have: privacy-enhancing technologies
- Nice to have: healthcare data
- Nice to have: finance data
- Nice to have: security data
