Daniel Huang

Senior Research Engineer at Snowflake

San Francisco Bay Area United States
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Summary

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Rockstar
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Daniel 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.
code2 years of coding experience
job4 years of employment as a software developer
bookUniversity of California, San Diego
bookBachelor's degree, Bachelor's degree at National Taiwan University
bookMaster 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
languagesChinese, English, Mandarin
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Github Skills (5)

machine-learning10
ai-agent10
llmops10
llm10
streamlit9

Programming languages (2)

Jupyter NotebookPython

Github contributions (4)

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truera/trulens

Jun 2024 - Mar 2026

Evaluation and Tracking for LLM Experiments and AI Agents
Contributions:6 releases, 479 reviews, 240 PRs in 1 year 9 months
ai-agentllmmachine-learningneural-networksexplainable-ml
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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