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Research Engineer, Privacy and Anonymization

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Research Engineer, Privacy and Anonymization in Others

  • Singapore, Singapore

Responsibilities

  • Build systems that detect PII, quasi-identifiers, credentials, and other sensitive information and transform it according to data type and downstream use case.
  • Develop and benchmark detection methods using rules, statistical models, classifiers, and LLM-based approaches.
  • Build production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic data generation.
  • Create evaluation frameworks for privacy risk and retained data 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.
  • Translate privacy requirements into technical policies and safeguards in collaboration with engineering, research, operations, and customers.

Requirements

  • Strong proficiency in Python and experience building reliable production data or ML systems.
  • Experience with information extraction, named-entity recognition, classification, or related techniques for detecting rare or sensitive content.
  • 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 subtle leakage paths, edge cases, and adversarial failure modes.
  • Experience building data-processing pipelines end-to-end without a fully prescribed roadmap.
  • Preferred: hands-on experience with differential privacy, k-anonymity, secure aggregation, format-preserving encryption, or other privacy-enhancing technologies.
  • Preferred: experience with sensitive healthcare, finance, or security data; low-latency or high-throughput ML inference; unstructured problem spaces; or early-stage startups.

Benefits

  • Full-time employment with offices in San Francisco and Singapore, with remote work available for candidates able to overlap 70–80% with either time zone.
  • Relocation and visa support for strong full-time candidates moving to the US or Singapore.
  • Competitive compensation.
  • 100% covered medical, dental, and vision insurance through Blue Shield of CA for US employees.
  • Lunch and dinner for in-office employees.
  • Company-wide holiday break from Christmas Eve through New Year’s Day, in addition to PTO and paid holidays.
  • Equinox membership, 401(k), and commuter benefits for US employees.
  • Unlimited access to tokens for ChatGPT, Claude Code, Cursor, and similar tools.
  • Applications are rolling; the process includes two technical interviews and a 2–3 day work trial.

Salary: Competitive

HUD

The platform to build RL environments. We help improve frontier models across diverse capabilities and help build post-training datasets for doing RFT.

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