Chang-hong Hsu
Senior Machine Learning Engineer - AI-X at Samsara
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolChang-hong Hsu is a Senior Machine Learning Engineer with 11 years of experience building production-grade AI and MLOps systems, currently leading development of Samsara Assistant—an agentic AI platform for the physical world. He specializes in dependable tool use and multi-step reasoning, combining hybrid RAG, programmatic prompting (DSPy/GEPA-style), and planner–executor patterns with privacy-by-design guardrails and human-in-the-loop review. His work spans end-to-end MLOps—feature/embedding pipelines, online inference, observability and drift monitoring—ensuring models deliver measurable business outcomes. Previously he drove contextual exploration at Pinterest and high-impact conversion and real-time forecasting models at Lyft, and contributed key SageMaker integrations and robustness improvements to the Flyte open-source orchestration project. With a PhD in Computer Engineering from the University of Michigan, Chang-hong’s strength is bridging ML innovation with systems-level performance to ship reliable, safe AI in production.
11 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Engineering, Doctor of Philosophy (PhD) Computer Engineering at University of MichiganMaster of Science (MS) Electrical Engineering, Master of Science (MS) Electrical Engineering at National Taiwan University
English, Chinese
Github Skills (20)
distributed-training10
python10
testing10
sagemaker10
automation10
mlops10
automations10
flyte9
mle8
ml8
data-science8
kubernetes7
dockers7
aws7
kubernetes-pods7
Programming languages (10)
Github contributions (5)
flyteorg/flytekit
Jun 2020 - Dec 2020
Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.
Role in this project:
MLOps Engineer
MLOps EngineerContributions:5 releases, 48 reviews, 251 commits in 6 months
Contributions summary:Chang-hong primarily contributed to enhancing the SageMaker integration within the Flyte ecosystem, focusing on supporting custom training jobs and enabling distributed training capabilities. They developed models for SageMaker proto messages and adapted training job models for distributed training. The user's contributions involved refactoring and unit testing, and also fixed bugs in existing implementations, ensuring the stability and functionality of the SageMaker tasks within Flyte.
flytepythondataflyte-taskspypi
bnsblue/awesome-dialogue-management
Sep 2016 - Sep 2016
Contributions:13 commits, 12 pushes, 1 branch in 4 days
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