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Zhiyu (Edward) Liang
Software Engineer · AI Systems
Open to meaningful engineering work
Software Engineer · AI Systems · Product Infrastructure

Zhiyu (Edward) Liang

I work across AI systems, backend infrastructure, and product engineering. Most of my projects live where software has to be technically serious, operationally reliable, and still useful to real people.

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Python Java Golang TypeScript LLMs Distributed Systems Kubernetes Spark

Current Focus

Building AI-enabled workflows, backend platform systems, and product-facing software where speed, reliability, and clarity all have to coexist.

Based In
California and Toronto
Background
Product engineering, ML systems, backend infrastructure
Interested In
AI infrastructure, developer tools, full-stack systems
Experience

Product, systems, and AI work in one timeline.

2023 - Present
Software Engineer, Digital Commerce Platform
Meta
Designed AI-enabled automation for complex internal workflows, led reliability work for high-risk backend APIs, and shipped ML-guided systems connected to retention and monetization surfaces.
Agentic Systems Backend APIs Reliability Monetization
2022 - 2023
Software Engineer, Shops Ads
Meta
Improved engineering quality and test culture, reduced rendering latency, and made critical commerce flows faster and more reliable across frontend and backend paths.
Product Engineering Performance Frontend + Backend
2018 - 2021
Machine Learning Engineer
Qualcomm
Built data pipelines for code and language model training, automated model conversion workflows, and worked on quantization techniques for efficient transformer deployment.
Spark GCP ONNX Quantization
2019
NLP Research Intern
Vector Institute
Prepared large-scale text corpora, implemented GPT-style models, and built distributed training tooling for language model research workflows.
NLP Distributed Training Research Tooling
Education

Formal background and technical foundation.

Academic foundation across systems, machine learning, and applied research.

Yale University

Master of Science in Computer Science
New Haven, CT
2021 - 2022

University of Toronto

Honours Bachelor of Science in Computer Science
Toronto, ON
2015 - 2019

Contact

Reach out if the overlap is real.

Best fit tends to be AI systems, backend-heavy product work, infrastructure for model-enabled applications, or engineer-generalist roles with real technical depth.

Best conversations are usually around AI systems, backend-heavy product work, or software roles that need someone comfortable moving between infrastructure and product constraints.

Email edwardlzy0@gmail.com
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