Teams at hud

HUD is accepting applications for exceptional candidates across research, engineering, go-to-market, and operations. Applicants must propose a specific contribution based on research into HUD and provide concrete evidence of exceptional ability and relevant experience. The role is full-time, based in San Francisco, Singapore, or remotely with substantial time-zone overlap. The hiring process includes two technical interviews and a two- to three-day work trial.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

Own end-to-end technical data and evaluation programs for frontier AI labs, coordinating requirements, milestones, vendors, quality assurance, delivery, and retrospectives. Translate ambiguous technical needs into executable plans, improve data quality and production workflows, manage cross-functional dependencies, and partner with research, platform, and marketplace teams to inform product improvements.