Summary
Deep Sidhpura is a Machine Learning Engineer with 11 years of experience specializing in deep learning and NLP, currently applying his expertise at TikTok in San Francisco. He has built production-grade transformer models and low-latency solutions at Amazon and developed large-scale, domain-adapted seq2seq models and robust adversarial spell-correction systems at eBay, leveraging PyTorch, Fairscale, and Hugging Face tooling. His background spans research and applied roles—from document QA, coreference and MT quality estimation to anomaly detection and bioinformatics—showing a strong ability to move models from research to high-precision production. A dual-degree engineer with top grades from University of Mumbai and an MS from USC, he combines academic rigor with practical optimization techniques like layer pruning and knowledge distillation. Notably, he led pre-training efforts on billion-example e-commerce data, demonstrating both data-scale engineering and model innovation for sensitive use cases.
11 years of coding experience
6 years of employment as a software developer
Master of Science (MS), Computer Science, 3.6/4.0, Master of Science (MS), Computer Science, 3.6/4.0 at University of Southern California
Bachelor’s Degree, Computer Engineering, 9.3 / 10, Bachelor’s Degree, Computer Engineering, 9.3 / 10 at University of Mumbai
English, Gujarati, Hindi