Research Engineer, Privacy and Anonymization (Pacific Time)
Pragmatike3 days ago
Remote, United States +9 moreMid Level
Responsibilities
- Build systems to detect PII, quasi-identifiers, credentials, secrets, and other sensitive information.
- Design data-type- and use-case-specific transformations such as redaction, masking, pseudonymization, or anonymization.
- Develop and benchmark rules-, statistical-model-, classifier-, and LLM-based detection approaches.
- Build production anonymization pipelines for data used in processing, training, evaluation, and synthetic data generation.
- Create evaluation frameworks covering privacy risk, retained utility, recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
- Design systems robust to new data sources, schema drift, unusual formats, and sensitive information in unexpected fields.
- Translate privacy requirements into technical policies and safeguards with engineering, research, operations, and customers.
Requirements
- Strong proficiency in Python and experience building reliable production data or machine-learning systems.
- Experience with information extraction, named-entity recognition, classification, or related sensitive-content detection methods.
- Ability to compare approaches across recall, precision, latency, cost, and downstream data utility.
- Understanding of redaction, masking, pseudonymization, anonymization, and synthetic data and when each is appropriate.
- Ability to reason about leakage paths, edge cases, adversarial failure modes, and privacy risk.
- Experience building end-to-end data-processing pipelines without a fully prescribed roadmap.
- Clear written and spoken English and comfort collaborating across teams and time zones.
- Preferred experience includes differential privacy, k-anonymity, secure aggregation, format-preserving encryption, sensitive healthcare, finance, or security data, high-throughput or low-latency ML inference, and taking research into production.
- Technical aptitude and learning potential are valued more than years of experience, and candidates need not meet every preferred qualification.
Benefits
- Full-time role starting ASAP.
- On-site work is available in San Francisco or Singapore, with remote work available from Singapore or US Pacific time zones.
- Remote candidates should overlap approximately 70–80% with San Francisco or Singapore business hours, with the daily schedule agreed during hiring.
- Opportunity to build systems that enable privacy-preserving AI training while retaining useful data structure and signal.
About Pragmatike
Pragmatike is a Paris-based IT services and recruiting firm connecting remote-first companies with software engineers and tech specialists worldwide. Founded in 2022, it places contractors or full-time hires and staffs teams to complete projects for startups and scaleups. The private partnership offers access to a large network of 50,000+ specialists across 60+ countries.