Research Engineer, Privacy and Anonymization

hud
San Francisco, Singapore
Workplace: OnsiteFull timeUSD 140,000 - 250,000 annuallyFunction: Research & Scientific (R&D)Experience: 3+ yearsSkills: ["Attention to detail","Experimental mindset","Analytical thinking","Collaboration","Communication"]

Build privacy and anonymization systems that protect sensitive real-world data before it enters processing, training, evaluation, and synthetic data pipelines. Detect and remove PII, secrets, and other sensitive content using rules, statistical models, classifiers, and LLM-based approaches. Create evaluation frameworks to measure privacy risk and retained utility, and ensure robustness to new sources, schema drift, and adversarial re-identification.

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FursaFursa
hud
hud
2 days ago

Research Engineer, Privacy and Anonymization

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build privacy and anonymization systems that protect sensitive real-world data before it enters processing, training, evaluation, and synthetic data pipelines. Detect and remove PII, secrets, and other sensitive content using rules, statistical models, classifiers, and LLM-based approaches. Create evaluation frameworks to measure privacy risk and retained utility, and ensure robustness to new sources, schema drift, and adversarial re-identification.
Location: San Francisco, Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information and design data-type-specific transformations.
  • •Develop and benchmark detection approaches combining rules, statistical models, classifiers, and LLM-based methods.
  • •Create production pipelines that anonymize raw data before downstream processing, training, evaluation, or synthetic data generation.
  • •Build evaluation frameworks that measure privacy risk and data utility, including recall-weighted metrics and leakage/adversarial re-identification tests.
  • •Design robust systems that handle new data sources, schema drift, unusual formats, and sensitive information in unexpected fields.

Pay and Benefits

Salary: USD 140,000 - 250,000 annually
Perks:Health InsuranceDentalVision401kGym MembershipCommuter BenefitsPaid Leave

Key Requirements

  • •Strong proficiency in Python and experience building reliable production data or ML systems.
  • •Experience with information extraction, named-entity recognition, classification, or related methods for detecting sensitive content.
  • •Ability to compare approaches using recall, precision, latency, cost, and downstream data utility.
  • •Understanding of redaction, masking, pseudonymization, anonymization, and synthetic data, and when each is appropriate.
  • •High attention to detail to reason about subtle leakage paths, edge cases, and adversarial failure modes.
Experience:3+ yearsMachine learningData privacyAIData pipelines
Skills:Attention to detailExperimental mindsetAnalytical thinkingCollaborationCommunication
Tech Stack:PythonLLM-based methodsNamed-entity recognitionClassificationChatGPTClaude CodeCursor

Eligibility

Nationality:US National

Company Brief

hud
Hud provides a lightweight developer-focused tool that captures and shares UI components and interactive design specs from the browser to streamline design-to-development handoff and collaboration between designers and engineers.
Industry: Developer Tools
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