Hai-anh Trinh
Tech Lead, SWE ML NLP at Grammarly
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolHai-anh Trinh is a Machine Learning Engineer with 16 years of experience building production AI, AutoML, and distributed systems, now at Apple after leading personalization and LLM initiatives at Grammarly. He has driven measurable user engagement and multimillion-dollar revenue impact through personalized ranking and agentic AI, and invented privacy-conscious methods to personalize LLM outputs. Previously he scaled Panasonic’s AutoML and anomaly-detection platforms to model billions of sequences and enabled Fortune 500 deployments including a low-latency NASDAQ collaboration. As Arimo’s founding engineer he created SmartQuery, an “Alexa for big data,” helping win the company’s first $1M customer and contributing to multiple patents across NLP, dataviz, and distributed analytics. A voracious learner and inventor with 10+ granted patents, he combines deep research-grade expertise with product-minded execution and hands-on open-source contributions that improve practical ML examples and tutorials. Based in Seattle, he thrives at the intersection of research, engineering, and product to deliver scalable, real-world AI systems.
16 years of coding experience
9 years of employment as a software developer
BA, Mathematics, Music, summa cum laude with honors, BA, Mathematics, Music, summa cum laude with honors at Macalester College
German, Vietnamese, English
Stackoverflow
1,162reputation
117kreached
8answers
1question
deep-learning
top-5%
keras
top-5%
Github Skills (20)
python10
machine-learning10
subprocess9
scikit9
scikit-learn9
deep-learning9
forecasting9
keras9
jupyter-notebook9
forecast9
automl8
data-science8
rank6
concurrency6
hive6
Programming languages (8)
Github contributions (5)
h1st-ai/h1st
Aug 2020 - Jan 2021
Power Tools for AI Engineers With Deadlines
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 59 commits, 9 PRs in 5 months
Contributions summary:Hai-anh's commits primarily focused on enhancing the existing forecasting and automotive cybersecurity examples within the H1st repository. Specifically, they modified the `forecast.py` file to handle Kaggle data and incorporated the use of `subprocess.run()` for executing external commands. Additionally, the user updated and expanded the automotive cybersecurity tutorial by incorporating a public dataset, modifying notebooks, and modifying graph to address "graph issue." These changes suggest a focus on improving the practical application and educational value of the project's AI and ML capabilities.
predictive-maintenancecollaborationhome-automationpower-toolsdatascience-environment
aht/extproc
Aug 2010 - Jun 2012
Contributions:57 commits in 1 year 10 months
execpythonpipeshell-scriptsredirection
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