Summary
Baolin L is an AI/ML engineer with a decade of experience building end-to-end machine learning systems across NLP, computer vision, and generative AI, specializing in scalable, cost-conscious production deployments. He has repeatedly turned low-data problems into production value—using synthetic labeling, prompt engineering, and PEFT/fine-tuning of Hugging Face and Gemini models—to enable semantic search, NER, multi-label classification, and image-ranking solutions that process tens of thousands of documents per quarter. Comfortable across cloud MLOps stacks (Vertex AI, SageMaker, Lambda) and tools like PyTorch, Label Studio, and Gradio, he bridges research prototyping and hardened APIs for client-facing demos. Past projects include migrating governance to unified model tracking, cutting vendor costs by 90% through in-house modeling, and shipping serverless classifiers with near-human accuracy. Based in San Diego, he blends an engineer’s pragmatism with research-driven innovation, often applying generative techniques to automate labeling and accelerate POCs.
10 years of coding experience
11 years of employment as a software developer
Westmoor High School
BS Civil Engineering, BS Civil Engineering at San José State University
Master’s Degree Master's in Data Science., Master’s Degree Master's in Data Science. at Galvanize - San Francisco, SoMa
Chinese, English