Research Engineer (AI Privacy)

Location: On-site in San Francisco or Singapore; remote candidates are considered with 70–80% working-hours overlap with either time zone. Relocation and visa support are available for strong full-time candidates moving to the US or Singapore.

Company

hirify.global builds infrastructure for RL training data and evaluations for frontier AI agents, including a marketplace for frontier labs, Fortune 500 companies, and startups.

What you will do

• Build systems to detect PII, quasi-identifiers, credentials, secrets, and other sensitive information.
• Design transformations that preserve useful structure and signal for downstream AI training.
• Develop and benchmark rules, statistical models, classifiers, and LLM-based detection methods.
• Build production anonymization pipelines for processing, training, evaluation, and synthetic data workflows.
• Create privacy and utility evaluation frameworks, including recall-weighted metrics, leakage tests, and adversarial re-identification attempts.
• Work with engineering, research, operations, and customers to translate privacy requirements into technical safeguards.

Requirements

• Strong Python proficiency and experience building reliable production data or ML systems.
• Experience with information extraction, named-entity recognition, classification, or related methods 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.
• Strong attention to detail when analyzing leakage paths, edge cases, and adversarial failure modes.
• Experience building end-to-end data-processing pipelines without a fully prescribed roadmap.

Nice to have

• Experience with differential privacy, k-anonymity, secure aggregation, format-preserving encryption, or other privacy-enhancing technologies.
• Experience handling sensitive healthcare, finance, or security data.
• Experience with low-latency or high-throughput ML inference and data-processing systems.
• Early-stage startup experience and strong cross-functional communication skills.

Culture & Benefits

• Mostly full-time, in-person team of approximately 25 people, with some remote employees.
• Competitive compensation and a technically focused team including AI startup founders, researchers, and International Olympiad medalists.
• US employees receive fully covered medical, dental, and vision insurance, plus 401(k) and commuter benefits.
• Office employees receive lunch and dinner, and all employees receive a company-wide holiday break in addition to PTO and paid holidays.
• Additional benefits include an Equinox membership and access to ChatGPT, Claude Code, Cursor, and similar tools.

Hiring process

• Applications are reviewed on a rolling basis.
• The process includes two technical interviews followed by a 2–3 day work trial.