Summary
Shaolong Chen is an Applied Scientist II in Sunnyvale with nine years of experience applying machine learning, deep learning and NLP to production problems. At Amazon and previously Carvana he built end-to-end deep learning pipelines, pretraining and deploying BERT at scale (including TPU pretraining, TensorFlow Serving, Docker and Kubernetes) and improved intent-classification accuracy by double-digit margins. He combines a physics PhD-level analytical background with hands-on engineering—optimizing inference latency from 800ms to 100ms and using techniques like temperature scaling to calibrate model probabilities. Comfortable across the research-to-production lifecycle, he blends advanced model design (GloVe, LSTM/GRU/CNN hybrids, BERT) with pragmatic data engineering and deployment skills. An implicit strength is his fluency converting messy SQL/BigQuery text data into robust features and taxonomies that drive measurable business impact.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS), Applied Physics, Bachelor of Science (BS), Applied Physics at Huazhong University of Science and Technology
PhD, Physics, PhD, Physics at University of California, Riverside