Summary
Tayyab Bin Tahir is a Software Engineer with 10 years of experience building high-performance, scalable systems at the intersection of AI, distributed systems, and cloud infrastructure. Currently leading generative AI and LLM infrastructure at Siemens, he has a track record of architecting production-grade ML solutions that optimize latency and reliability across AWS and Azure. His background spans enterprise and research: from delivering an AI distributed data search engine at BD that handled 100M+ requests to publishing applied adversarial ML work while at the University of Oregon. He combines deep systems expertise (Spark, Kafka, Kubernetes, Open MPI) with hands-on modeling (PyTorch, TensorFlow) to move models from prototype to resilient production. Passionate about responsible AI, he embeds guardrails and evaluation frameworks into deployments to ensure ethical, measurable impact. Based in Sunnyvale, he blends startup-scale delivery and Fortune 500 rigor, and often surfaces non-obvious wins such as memory- and latency-driven refactors that doubled performance in legacy systems.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of Oregon
Specialization Courses Data Science Cloud Computing Distributed Computing, Specialization Courses Data Science Cloud Computing Distributed Computing at Coursera
FSc Pre-Engineering, FSc Pre-Engineering at Government College University (GCU), Lahore
Matriculation in Science, Matriculation in Science at Divisional Public School Model Town Lahore
Bachelor of Science in Computer Science Computer Science, Bachelor of Science in Computer Science Computer Science at National University of Computer and Emerging Sciences
English, Urdu, Punjabi, German