layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Software Engineer, Data Quality at HUD

Build full-stack tools for reviewing tasks, inspecting agent trajectories, checking graders, and investigating data quality issues
Create dashboards and metrics that show quality trends, failure modes, and the health of review and validation workflows
Design backend services, APIs, and data workflows that connect quality checks with task creation, evaluation, and feedback to data creators
Work with QNI and research engineers to turn evolving review methods into clear, efficient workflows that scale beyond manual analysis
Move proven internal tools into production, improving their reliability, usability, and observability as adoption grows
Investigate issues in live workflows and use what you learn to improve the platform and prevent repeat failures
Experience
You may be a good fit if you have: 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
Strong candidates may also have: 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 & company details
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.

Software Engineer, Data Quality

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