Gurinder Chauhan is a Staff ML/MLOps Engineer with a decade of experience building production-grade AI systems across medical, bioinformatics, automotive, retail, and healthcare domains. He blends deep learning and classical ML expertise—NLP, computer vision, recommendation systems—with hands-on GPU programming (CUDA/OpenCL) and cloud-native MLOps, having deployed LangFlow-based agentic pipelines, Kubernetes/ArgoCD workflows, and observability stacks. Notable work includes architecting multilingual Document Intelligence and hybrid RAG systems that fuse knowledge graphs (NebulaGraph) with vector stores (Qdrant) to deliver explainable, grounded responses and reduce manual effort by 80%. He has a strong background in end-to-end model engineering from custom YOLOv5 pipelines for multi-stream video inference to LLM-driven knowledge ingestion and automated schema generation. Comfortable in Python, C/C++, MATLAB, and assembly, he pairs research-rooted bioinformatics experience with pragmatic automation and orchestration to move complex ML projects into reliable production. Based in Los Angeles with an MS in Electrical Engineering, he often combines symbolic and semantic approaches to make ML systems both accurate and auditable.
10 years of coding experience
9 years of employment as a software developer
IK Gujral Punjab Technical University
Master of Science (MS) Electrical Engineering, Master of Science (MS) Electrical Engineering at Loyola Marymount University
Contributions:4 releases, 18 commits, 1 PR in 2 months
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Gurinder Chauhan - Staff ML MLOps Engineer at Ybor Technology, LLC