Anthony Fong is a backend-focused software engineer with eight years of experience building scalable, production-grade systems across finance and consumer tech. He has shipped backend and reliability work at Citadel and Meta, and contributed to payments risk systems at TikTok, demonstrating a blend of low-latency engineering and operational rigor. Comfortable across distributed systems, ML-informed products, and orchestration tooling, he has implemented workflow scheduling, monitoring, and deployment pipelines using tools like Docker, Kubernetes, Prometheus, Airflow, and Prefect. A current NTU Renaissance Engineering student based in New York, Anthony combines strong academic foundations with practical experience in machine learning and quantitative finance—evident from early ML projects that delivered near-SOTA results on medical image benchmarks. Colleagues describe him as someone who moves easily between research-grade models and hard production constraints, making him effective at turning prototypes into resilient services.
8 years of coding experience
5 years of employment as a software developer
A levels, A levels at Dunman High School
Renaissance Engineering Engineering, Renaissance Engineering Engineering at Nanyang Technological University Singapore
Python repository implementing quantitative finance models used to create analyze portfolios, and construct portfolio
Contributions:17 commits, 10 PRs, 17 pushes in 3 days
pythonfinancial-dataedgarsecportfolios
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