Research Engineer, Privacy and Anonymization

The role

You will build privacy and anonymization systems to make sensitive real-world data safe for AI training. You will develop methods to detect and remove PII and other sensitive information from raw data.

What you will do

• Build systems to detect PII, quasi-identifiers, credentials, and other sensitive information
• Design transformations based on the data type and downstream use case
• Develop and benchmark detection approaches using rules, statistical models, classifiers, and LLM-based methods
• Build production pipelines that anonymize raw data
• Create evaluation frameworks to measure privacy risk and retained data utility
• Design systems that remain robust to new data sources, schema drift, and unusual formats
• Work with engineering, research, operations, and customers to translate privacy requirements into technical policies

Required qualifications

• Strong proficiency in Python
• Experience building reliable production data or ML systems
• Experience with information extraction, named-entity recognition, classification, or related methods
• Strong experimental instincts to compare approaches across recall, precision, latency, cost, and downstream data utility
• An understanding of the difference between redaction, masking, pseudonymization, anonymization, and synthetic data
• High attention to detail regarding leakage paths, edge cases, and adversarial failure modes
• Built data processing pipelines end-to-end without a fully prescribed roadmap

Nice to have

• Hands-on experience with privacy-enhancing technologies such as differential privacy, k-anonymity, secure aggregation, format-preserving encryption, etc.
• Worked with sensitive data in areas such as healthcare, finance, or security
• Built low-latency or high-throughput ML inference and data-processing systems
• Worked in unstructured problem spaces and take ownership from early research through production deployment
• Early-stage startup experience
• Strong communication skills for collaboration across teams and time zones

Benefits

• Competitive compensation
• 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees)
• Lunch and dinner for in-office employees
• Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays
• 401k with a 4% match
• Equinox membership and commuter benefits (US employees)
• Health/wellness stipend (Singapore employees)
• Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
• Annual travel budget to visit either office

Before you apply

• Provide support for relocation and visas for strong full-time candidates to the US or Singapore
• The process includes 2 technical interviews and a 2-3 day work trial

About the company

HUD's mission is to build reliable, fair and open infrastructure for AI data. The team is a growing group of researchers, engineers and operators backed by $16M from top VCs and YC.