Daniel Huang
Machine Learning Engineer at Snowflake
San Francisco Bay Area United States
Summary
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Rockstar🎓
Top SchoolDaniel Huang is a Machine Learning Engineer based in the San Francisco Bay Area with two years of industry ML experience and a strong foundation in distributed systems and backend engineering. He helped scale and operationalize ML observability and evaluation at TruEra (acquired by Snowflake) after building production-grade services at LotusFlare and security-focused systems at Amazon. Trained at Carnegie Mellon’s Language Technologies Institute and with a BS in Math-CompSci from UC San Diego, he blends research-informed ML explainability work with practical platform skills like Kubernetes, Kafka, and microservices. Notably, his background spans both product-focused teleco platforms serving millions of monthly users and rigorous LLM benchmarking, giving him a rare combination of reliability engineering and model-centric expertise.
1 year of coding experience
6 years of employment as a software developer
University of California, San DiegoBachelor's degree, Bachelor's degree at National Taiwan UniversityMaster of Science - Computer Science Language Technologies Institute @ School of Computer Science, Master of Science - Computer Science Language Technologies Institute @ School of Computer Science at Carnegie Mellon University
Chinese, English, Mandarin
Github Skills (8)
pytorch10
machine-learning10
evaluation-framework10
interpretation10
deep-learning10
llmops10
evaluation10
llm10
Programming languages (1)
Github contributions (4)
truera/trulens
Jun 2024 - Apr 2025
Evaluation and Tracking for LLM Experiments
Contributions:1 release, 336 reviews, 168 PRs in 10 months
explainable-mlpytorchevaluation-frameworkdeep-learningnets
sfc-gh-apgupta/snowvation2024-crewAI-examples
Dec 2024 - Dec 2024
A collection of examples that show how to use CrewAI framework to automate workflows.
Contributions:2 PRs, 7 pushes, 1 branch in 1 day
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