Huong Ngo is a Member of Technical Staff in Seattle with eight years of experience transitioning from business roles into front-end and data-focused engineering. She blends applied ML research—contributing to large-scale embodied AI datasets and fine-tuning ViT models—with practical data engineering wins, such as a PySpark ETL that converted 3M rows of Excel data and cut processing time by 97%. Comfortable across the stack, Huong has built production data pipelines in Azure Synapse, orchestrated batch jobs, and designed scalable schemas and analytics integrations for product teams. Her background includes teaching core CS courses and collaborating on research at the Paul G. Allen School and AI2, reflecting a strong mix of mentorship, reproducible research, and product impact. Notably, she leverages CLIP and vision-transformer tooling to automate costly manual labeling, demonstrating an eye for automating labor-intensive workflows.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Data Science and Statistics, Bachelor of Science - BS, Data Science and Statistics at University of Washington
A React app fetching dad's jokes lets audience rate jokes, the emoji will change according to number of upvotes and downvotes.
Contributions:22 commits, 1 push in 16 days
upvotesemojireactdadjavascript
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