Summary
Abdullah Siddique is a Machine Learning Engineer with eight years of experience building production ML systems, currently focused on recommendation systems at LinkedIn in San Francisco. He holds an MS in Computer Science from Columbia and has a strong track record shipping computer-vision and deep learning features for consumer products at Tempo, including rep-counting, form guidance, equipment detection, and weight classification. Abdullah combines research experience—from ultrasound simulation and point-cloud reconstruction to oceanography image classification—with hands-on MLOps skills, creating tooling for data ingestion, cleaning, parameter tuning, and performance testing in production. Earlier roles at Afiniti and research labs honed his ability to translate model gains into measurable business impact and to optimize legacy systems for real-time constraints. Notably, he has repeatedly helped grow and coordinate globally distributed teams while moving prototypes into scalable product features.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Lahore University of Management Sciences
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Columbia University