HUD - Lead Research Engineer, Data Quality
Requirements
• Advanced proficiency in Python, Docker, and Linux environments • Deep intuition for data quality - you can reason about what makes tasks realistic, learnable, diverse, reliable, and useful for training • Experience building QC systems, evals, benchmarks, synthetic data pipelines, validation workflows, or model evaluation infrastructure • Comfort working across messy human and technical systems, including domain experts, vendors, generated data, model outputs, graders, and infrastructure • Strong written communication and the ability to explain methodology clearly to researchers, engineers, labs, and external audiences • Strong candidates may also have: • Experience leading teams on ambiguous technical projects from problem definition through implementation and iteration • Experience working with subject-matter experts to capture domain judgment and convert it into scalable review or generation systems • Be comfortable designing metrics, experiments, and QA/QC processes, not just executing them • Early-stage startup experience with ability to work independently in fast-paced environments • Be detail-oriented and able to spot subtle inconsistencies or edge cases in data • Team & company details • Team Size: ~15 people currently, mostly full-time in-person, but some remote. • Team Size • Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. • Our team: • Company stage: We have 8 figures in funding and high revenue growth. We’re scaling profitably and quickly to meet very strong demand. • Company stage: • Logistics • Logistics • Employment: Full-time. • Employment • Location: On-site only, for now. You can join the team in the San Francisco Bay Area or Singapore offices. • Location • 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. • Timeline
Responsibilities
• Lead HUD’s data quality strategy including building QC systems, defining and enforcing quality standards, and designing experiments to grade agent outputs • Develop new methods for validating synthetic data at scale, such as failure-mode analysis, task mutation checks, and trajectory auditing • Partner with research engineers, domain experts, and data vendors to diagnose quality issues and improve data generation workflows • Turn qualitative research insights into production systems, internal tools, dashboards, validation pipelines, and feedback loops • Help build internal research taste around what makes agent training data actually useful, not just superficially correct • Mentor other research engineers to maintain a high bar for technical rigor, clarity, and execution speed
Benefits
• Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • We will contact you via this email during the application process. • or drag and drop here • Please ensure to provide your LinkedIn profile or Resume, we require at least one of the two. • Or any other examples of technical experience (Codeforces / Leetcode etc.) • Or Arxiv, OpenReview, Hugging Face etc. • Or anything else we'd find interesting. • Or something you did that you were proud of. Be specific. • Enter your current location. This is mainly for coordinating calls/meetings for the application process, and for any future logistics. • Select “Yes” if the position is exclusively on‑site, AND you will need employer sponsorship to obtain or maintain legal authorization to work in that location. • “Yes” • exclusively on‑site, • Select “No” if the role offers a remote option you intend to take, OR you already have, or can independently secure, authorization to work on-site without employer assistance. • remote • without • Your response is gathered solely to understand potential immigration requirements. It will not disqualify you from consideration. If you are selected for the role, we will work with you, consistent with applicable laws and company policies, to pursue any required sponsorship. • Anything else you want us to know, or any questions/feedback.
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