Santhosh C.

I am a Python-focused AI Engineer with over 5 years of combined experience in deep learning, computer vision, and large language model (LLM) prototyping. My work spans building front-end UIs for machine vision systems, developing CNN-based diagnostic pipelines, and architecting privacy-first Retrieval-Augmented Generation (RAG) systems for domain-specific workflows. I have hands-on expertise in PyTorch, TensorFlow, Keras, and Scikit-learn, with a strong foundation in supervised, unsupervised, and reinforcement learning techniques. My recent projects include a hybrid AI veterinary radiograph analyzer (CNN + XGBoost) and a local-first oncology RAG assistant integrating llama.cpp for secure, on-premise medical data processing. My approach blends research-grade experimentation with production-ready engineering. I am deeply familiar with model evaluation (Evals), fine-tuning (SFT), and human feedback loops (RLHF), and can rapidly adapt to cutting-edge tools and architectures. Employers value my ability to work independently in high-pressure, mission-critical environments, my strong communication skills for cross-functional collaboration, and my commitment to delivering measurable impact. I thrive in remote-first, globally distributed teams and am passionate about building AI systems that combine accuracy, privacy, and real-world utility.