Anindita Chavan is a Machine Learning Engineer with 9 years of experience building production-grade AI systems, currently developing advanced computer-vision solutions for the semiconductor supply chain at Smith & Associates. She architects hybrid anomaly-detection pipelines that combine traditional image processing with autoencoders and Vision Transformers, and builds LLM-orchestrated, agentic applications and RAG frameworks to surface actionable insights for buyers and sellers. Her research background blends deep learning and neuroscience—her LSTM work at Rutgers Robert Wood Johnson Medical School led to a publication in Scientific Reports—and complements a strong applied foundation from a MS in Computer Science (Machine Learning) at Rutgers. Previously she delivered backend and data-science projects at Citi and bridges research rigor with product-focused engineering, often implementing end-to-end Node.js and PyTorch solutions. A less obvious strength is her ability to move between low-level algorithm design and production deployment, making her effective at shipping robust, research-informed ML products.
Bachelor of Engineering - BE, Information Technology, 8.42/10, Bachelor of Engineering - BE, Information Technology, 8.42/10 at MKSSS Cummins College of Engineering for Women
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Anindita Chavan - Machine Learning Engineer at Smith & Associates