Shreyash Gaur

I am a machine learning engineer focused on building production-ready generative AI systems, retrieval-augmented pipelines, and scalable deployments on cloud platforms. I specialize in combining graph and vector retrieval for privacy-preserving, high-accuracy knowledge systems.

At Capgemini I architected multi-agent RAG solutions and event-driven model deployments on Azure Kubernetes Service, reducing manual effort and client support queries. I build multi-agent systems for automated analysis, migration tooling, and ROI simulations that materially improve business decision speed.

During an internship at Uptricks, I developed large-scale SKU clustering and automated damage-detection pipelines, achieving high clustering precision and improving classification accuracy using efficient neural architectures and FAISS similarity search. I deploy real-time inference via managed cloud endpoints and integrate pipelines with data warehouses.

I hold cloud and ML certifications (Google Cloud Professional ML Engineer, multiple Azure AI/Data certs, DeepLearning.AI specializations) and enjoy optimizing model training (LoRA/QLoRA), building hybrid retrieval systems with Neo4j and vector stores, and delivering reproducible, resource-efficient solutions.