Ting Yang is a Technical Lead with 7 years of experience building high-performance distributed systems and production AI infrastructure, currently focused on ML systems and LLM training at ByteDance. Previously at Google she helped design a low-latency serving platform that handled hundreds of terabytes and hundreds of millions QPS, cutting CPU costs by over 50% and earning internal recognition. She has led end-to-end ML platform efforts at Apple and AmmoAI, combining real-time agent orchestration, secure scalable APIs, and workflow automation. Comfortable moving between deep performance optimization and higher-level platform design, she routinely ships monitoring, experiment safety, and autoscaling features for mission-critical services. Based in San Jose, she pairs rigorous academic foundations from Peking University with hands-on leadership in fast-moving AI teams. A practical builder with a taste for tooling (paas tools on GitHub), she favors pragmatic, observable systems that keep AI models useful in production.
7 years of coding experience
12 years of employment as a software developer
Master's degree, Computer Software and Theory, Master's degree, Computer Software and Theory at Peking University
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