Saurav Bandral
Engineering Manager- Ai Ml @Cashify
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WORK HISTORY
Engineering Manager- Ai Ml @Cashify
Gurugram, IN
EDUCATION
Government college of Engineering and technology, Jammu
Bachelor of Engineering - BE, Electronics and Communications Engineering
ABOUT SAURAV BANDRAL
I build and scale production-grade AI systems that operate beyond the lab — in warehouses, factories, retail stores, and real-world mobile environments.With 7+ years in computer vision and applied AI, I have led the development of industrial inspection systems, AR/try-on platforms, and hardware-integrated ML pipelines across manufacturing, retail, and mobile ecosystems.Currently working as an Engineering Manager – AI/ML, I lead a 45+ member cross-functional organization spanning ML engineering, MLOps, backend systems, and large-scale annotation operations.Across my career, I have:• Productized image-based defect detection systems (16 defects, 32 categories, 95% accuracy) • Designed hardware-aware image acquisition systems across warehouse and retail environments • Built AR/try-on solutions (braces, shoes, flooring, makeup) deployed via Android and server APIs • Delivered industrial inspection and safety automation systems for clients including Mahindra and Nippon Paint • Developed object detection, segmentation, tracking, and rendering pipelines for production use • Reviewed 700+ pull requests to maintain architectural integrity and engineering standards I specialize in building **data-centric AI systems**, including annotation workflows, evaluation pipelines, and post-deployment feedback loops that ensure reliability of ML systems in real-world environments.More recently, I have been building and exploring **LLM and agentic AI systems**, including:• Agentic AI workflows using MCP integrating Jira and GitHub for automated PR validation and code review • LLM-powered code intelligence systems indexing repositories for Q&A and feature implementation guidance • Retrieval Augmented Generation (RAG) systems • LLM orchestration using LangChain and LangGraph for agent workflows I’m particularly interested in how **LLMs and agents can augment real-world AI systems**, combining perception models, structured data, and reasoning capabilities.Leadership philosophy: Strong technical depth. Clear ownership. Systems thinking. Teams that ship.Open to conversations around:• Engineering Leadership – AI / ML / Generative AI • LLM Platforms and Agentic AI Systems • Computer Vision & Applied AI Systems • Data-centric AI systems and ML infrastructure • Scalable Production ML Platforms Let’s connect.
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