Summary
Yifan Liu is a pragmatic software engineer and recent Michigan grad now pursuing an MS in Computer Science at UC San Diego, with three years of hands-on experience building full-stack systems and production AI services. He has delivered scalable features at TikTok, including an IDE plugin used by 5,000+ developers that cut unit-test authoring time by 85%, and engineered efficient PSI-based context extraction and streaming model integrations to achieve low-latency, secure inference. At startups he built customer-service and image-generation platforms processing millions of logs and 100k+ records, fine-tuned large LLMs (Qwen series) with LoRA to cut loss and inference time substantially, and deployed RAG/agent pipelines with sub-0.2s response times. Comfortable across C/C++, Python, OCaml, and JavaScript, he pairs systems-level performance tuning (runtime caps, token pruning, payload compression) with practical ML engineering and async production deployments. Notably, he combines deep implementation skill with a penchant for measurable impact — speeding workflows and trimming resource use rather than just prototyping features.
3 years of coding experience
1 year of employment as a software developer
University of California, San Diego
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University of Michigan
Bachelor's degree Electrical and Computer Engineering, Bachelor's degree Electrical and Computer Engineering at Shanghai Jiao Tong University