Bassam Arshad is a Data Scientist with 10 years of experience building low-latency, production-grade ML systems across computer vision, robotics, and large language model workflows. He has led interdisciplinary teams to deliver end-to-end solutions—from sensor and 3D point-cloud algorithms to RAG-enabled LLM chatbots—at companies including Zebra Technologies and Walgreens Boots Alliance. His work blends deep research (patented 3D sensing and segmentation techniques) with pragmatic MLOps and event-driven architectures that power real-time retail and logistics applications. Currently focused on optimizing coherence, reliability, and latency for GenAI/LLM pipelines, he pairs hands-on engineering (C++, Python, CUDA, PyTorch/TensorFlow) with a proven track record of deploying systems to GCP. Colleagues describe him as a pragmatic innovator who turns complex multimodal data into actionable, deployable intelligence.
9 years of coding experience
8 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at The University of Texas Rio Grande Valley
St. Thomas' College, Dehradun
International Indian School, Dammam
B.E Electronics and Communication Engineering, B.E Electronics and Communication Engineering at Visvesvaraya Technological University
Contributions:31 commits, 29 pushes, 2 branches in 1 year 11 months
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