New York, United States
Onsang is a product-focused software engineer and AI strategist with experience leading complex, data-driven initiatives across generative AI, automation platforms, and global operations. She brings a unique blend of product management, software engineering, and machine learning fluency, shaped by roles at Scale AI, Tesla, NASA, LG Electronics, and health tech startups. At Scale AI, Onsang led the product delivery of an agentic evaluation workflow from 0 to 1, supporting a $X.X million research partnership with top-tier AI labs. She built real-time dashboards using SQL and Python, and applied strategies to double throughput across 24/7 labeling workflows. She also restructured a full-stack labeling pipeline that recovered $X million in revenue and collaborated with cross-functional teams to scope legal risk, define LLM evaluation metrics, and implement productized workflows in the emerging agentic AI space. At Tesla, she shipped 11 major product initiatives for a document automation system supporting 1.3 million annual vehicle deliveries and 1 million documents processed per day. Her work cut funding delays by X days, saved XXXX man-hours per year, and resolved over €XX.X million in processing bottlenecks. She scoped AI automation initiatives with internal AI teams and drove international feature adoption, cross-border compliance, and cost reductions through platform-level enhancements. Onsang has also benchmarked conversational AI tools for NASA, led a 30-person product team at Horizon Labs, built EV energy forecasting models at LG, and won top honors at NASA Space Apps and Harvard’s Health System Innovation Lab Hackathon at the global level. She is technically fluent in full-stack development, Python, SQL, and machine learning infrastructure, and experienced in Agile delivery, roadmap planning, and data storytelling. With a master’s degree in Computer and Information Technology from Penn Engineering and a pre-vet research and digital agriculture background from Cornell, Onsang excels in fast-moving, cross-disciplinary environments where AI and systems innovation meet real-world outcomes.