surge-ai - Human Data Architect
Requirements
• Experience designing human data collection at scale — e.g., in computational cognitive science, HCI, crowdsourcing research, or a similar field where you've thought carefully about how to get reliable signal from human participants. • Familiarity with ML post-training paradigms (e.g., SFT, RL) and a working intuition for how data quality decisions map onto model outcomes. • Systems-level thinking — you understand how task design choices propagate into training data and you design accordingly. • Excellent communication skills — you can explain measurement concepts to engineers and engineering constraints to researchers.
Responsibilities
• Architect end-to-end data workflows — from task design through quality assurance and delivery — ensuring each stage produces data that is well-structured for its post-training purpose (e.g., SFT, RL, model evaluation). • Design collection structures and task frameworks that translate what clients need from a model into concrete, scalable data generation processes. • Build and monitor data quality frameworks that catch problems before they reach the client. • Partner with engineering and product teams to improve data pipelines, identifying where structural or methodological changes can improve throughput without sacrificing quality. • Translate patterns in data quality and project structure into actionable insights that inform project design, client deliverables, and product development.
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