Software Engineer, Data Quality

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.

We’re looking for a Software Engineer, Data Quality to build the tools that help HUD’s Quality and Intelligence (QNI) team assess and improve training data and evals for frontier agents. You’ll turn hands-on quality workflows into reliable internal products, then bring the most useful capabilities into HUD’s production platform.

You’ll work closely with QNI and research engineers across task review, trajectory inspection, grader checks, quality metrics, and feedback to data creators. The work spans interfaces, backend services, and data workflows, with a focus on making quality issues easier to find, understand, and fix.

Strong software engineering fundamentals and the ability to build across frontend, backend, and data systems

Proficiency in Python and a modern web stack such as TypeScript and React, or comparable tools

Built internal or user-facing products end-to-end, from understanding a workflow through shipping and improving it

Sound judgment about APIs, data models, and production systems, including how to make them reliable and easy to debug

An ability to turn ambiguous quality problems into useful interfaces, automation, and measurable checks

Clear communication and comfort working closely with research and quality teams to understand how people use the tools you build

Built tooling for data review, annotation, evals, benchmarks, or ML workflows

Worked with agent traces, graders, reward signals, or RL training data

Designed dashboards, observability tools, or review workflows for complex datasets and pipelines

Improved a prototype or internal tool until it was ready for wider production use

We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria.

Team Size : ~25 people currently, mostly full-time in-person, but some remote.

Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc.

Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand.

Employment : Full-time.

Location : We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones.

Visa Sponsorship : We provide support for relocation and visas for strong full-time candidates to the US or Singapore.

Timeline : Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial.