Ridhima Garg is a Senior AI Engineer with 10 years of hands-on experience building and deploying ML and deep learning systems across computer vision, NLP, and generative AI. She has driven production-ready solutions from microscopy image compression and RCNN-based instance segmentation at ZEISS to insurance OCR and deployment on AWS, and most recently has focused on LLM frameworks, PEFT fine-tuning, automatic prompt engineering and RAG enhancements. Her research background (MSc Data Science) and a published AAAI AICS paper on GlyphNet—achieving 0.92 AUC for homoglyph detection—underscore a strong blend of academic rigor and applied research. Comfortable across cloud platforms (Azure, AWS, GCP) and tools like LangChain and HuggingFace, she pairs model optimization (pruning, quantization) with CI/CD and Kubernetes deployments. Colleagues describe her as a pragmatic problem-solver who translates mathematical foundations into scalable products, and she quietly contributes to open-source tooling and practical image-format libraries. Based in Stuttgart, she seeks collaborations that push AI toward robust, real-world impact.
9 years of coding experience
5 years of employment as a software developer
10th Maths and Science, 10th Maths and Science at UNIVERSITY MODEL SCHOOL
Master of Science - MS Data Science, Master of Science - MS Data Science at FAU Erlangen-Nürnberg
12th Maths plus Computer Science, 12th Maths plus Computer Science at ESS ESS Convent School, Agra
Bachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at Dr. A.P.J. Abdul Kalam Technical University
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Ridhima Garg - Senior AI Engineer at Flick Gocke Schaumburg