Hire the Best Deep Neural Networks Developers
in India

I am an AI Engineer with 4+ years of experience building and deploying production-ready AI systems across classical machine learning, deep learning, computer vision, NLP, and Generative AI. Unlike many AI developers who focus only on LLMs, I work across the entire AI stack. I believe the best solution isn't always a large language model or an expensive API. Many real-world problems are better solved using classical machine learning or deep learning, resulting in lower infrastructure costs, faster inference, reduced latency, and greater control over your solution. My goal is always to build the most effective system not the most expensive one. Some of the areas I regularly work in include: * Classical Machine Learning (XGBoost, LightGBM, CatBoost, Random Forests, SVMs, feature engineering, predictive modelling, forecasting, anomaly detection, recommendation systems) * Deep Learning (PyTorch, TensorFlow, CNNs, Transformers, Vision Transformers, knowledge distillation, model optimization) * Computer Vision (object detection, image classification, segmentation, OCR, document understanding, face recognition, multi-object tracking, embedding-based search) * NLP & LLMs (RAG, GraphRAG, agentic workflows, fine-tuning, embeddings, semantic search, document QA, information extraction) * Generative AI applications using OpenAI, Anthropic, Gemini, and open-source models * End-to-end AI pipelines from data collection and preprocessing to training, evaluation, deployment, and monitoring I also have extensive experience optimizing AI models for production through knowledge distillation, pruning, quantization, and efficient inference, making models smaller, faster, and more cost-effective for both cloud and edge deployments. On the engineering side, I work comfortably with Python, FastAPI, PostgreSQL, pgvector, asynchronous programming, Docker, GPU acceleration, and cloud deployments. I build complete AI products and APIs that are designed to scale not just research prototypes. Beyond implementation, I enjoy solving difficult research and engineering problems. Whether it's designing a predictive model, improving model accuracy, reducing inference costs, building an intelligent document processing pipeline, or deploying an LLM application, I focus on solutions that are reliable, maintainable, and practical for production. I also lead a team of AI engineers, giving me experience not only in technical execution but also in planning, code quality, mentoring, and delivering projects on time. If you're looking for someone who can understand the problem first, choose the right AI approach, and build a production-ready solution that balances performance, cost, and scalability, I'd be happy to help.

I am an AI Researcher with numerous publications including IEEE TNNLS, MICCAI, CBMS, etc. I also have a YouTube channel named "Idiot Developer", where I upload videos related to deep learning. I also write blog posts on my website idiotdeveloper.com. ✅ Projects: 1. Human Face Landmark Detection - using pre-trained MobileNetv2 2. Multiclass Face Segmentation - using UNET. 3. Dog Breed Classification - using pre-trained ResNet50 4. Human Parsing using Crowd Instance-level Human Parsing (CHIP) dataset 5. Brain Tumor Segmentation 6. GAN to generate Anime 7. Retina Blood Vessels 8. Background Removal from Human Images and Videos 9. Implemented various segmentation architectures: U-Net, ResU-Net, DeepLabV3+, DoubleUNet, U2-Net and more. 10. Lung Segmentation 11 Autoencoders

𝐏𝐲𝐭𝐡𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐚𝐧𝐝 𝐓𝐮𝐭𝐨𝐫 | 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭 | 𝐋𝐚𝐫𝐠𝐞 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌𝐬) 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 | 𝐑𝐚𝐠 𝐚𝐧𝐝 𝐅𝐢𝐧𝐞-𝐭𝐮𝐧𝐢𝐧𝐠 | 𝐀𝐈 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 | 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐆𝐫𝐞𝐞𝐭𝐢𝐧𝐠 , 𝐈’𝐦 𝐕𝐢𝐠𝐧𝐞𝐬𝐡𝐰𝐚𝐫𝐚𝐧 𝐚𝐧 𝐀𝐈 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐨𝐫 𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐢𝐦𝐩𝐚𝐜𝐭 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐝𝐞𝐞𝐩 𝐞𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧, 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬, 𝐚𝐧𝐝 𝐋𝐋𝐌𝐬. 𝐈’𝐯𝐞 𝐛𝐮𝐢𝐥𝐭 𝐜𝐮𝐭𝐭𝐢𝐧𝐠-𝐞𝐝𝐠𝐞 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞𝐬, 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬, 𝐚𝐧𝐝 𝐡𝐢𝐠𝐡-𝐟𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 𝐭𝐫𝐚𝐝𝐢𝐧𝐠, 𝐜𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭𝐥𝐲 𝐡𝐞𝐥𝐩𝐢𝐧𝐠 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐞 𝐭𝐡𝐞𝐢𝐫 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐑&𝐃 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 🚨 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐇𝐢𝐫𝐞 𝐌𝐞 ✅ 𝐅𝐮𝐥𝐥-𝐭𝐢𝐦𝐞 𝐅𝐫𝐞𝐞𝐥𝐚𝐧𝐜𝐞𝐫 — 𝟓𝟎+ 𝐡𝐫𝐬/𝐰𝐞𝐞𝐤 | 𝐅𝐥𝐞𝐱𝐢𝐛𝐥𝐞 𝐚𝐜𝐫𝐨𝐬𝐬 𝐚𝐥𝐥 𝐭𝐢𝐦𝐞 𝐳𝐨𝐧𝐞𝐬. ✅ 𝐄𝐧𝐝-𝐭𝐨-𝐄𝐧𝐝 𝐎𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩 — 𝐟𝐫𝐨𝐦 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐫𝐨𝐛𝐮𝐬𝐭 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐭𝐨 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐌𝐋 𝐦𝐨𝐝𝐞𝐥𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐜𝐥𝐨𝐮𝐝. ✅ 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐑𝐞𝐚𝐝𝐲 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 — 𝐧𝐨 𝐦𝐨𝐫𝐞 “𝐰𝐨𝐫𝐤𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐥𝐚𝐛, 𝐟𝐚𝐢𝐥𝐬 𝐢𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧.” 𝐌𝐲 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧 𝟗𝟗.𝟗% 𝐮𝐩𝐭𝐢𝐦𝐞 𝐚𝐧𝐝 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐦𝐩𝐚𝐜𝐭. 𝐝𝐨𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 — 𝐈 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐬𝐞𝐚𝐦𝐥𝐞𝐬𝐬𝐥𝐲 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬, 𝐞𝐧𝐬𝐮𝐫𝐢𝐧𝐠 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐚𝐧𝐝 𝐥𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 & 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 ✅ 𝐀𝐈 & 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐮𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰, 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐌𝐋 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬 𝐭𝐚𝐢𝐥𝐨𝐫𝐞𝐝 𝐟𝐨𝐫 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐧𝐞𝐞𝐝𝐬. ✅ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐝𝐚𝐭𝐚 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐬𝐭𝐨𝐫𝐞𝐬, 𝐚𝐧𝐝 𝐄𝐓𝐋 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 𝐟𝐨𝐫 𝐡𝐢𝐠𝐡-𝐯𝐨𝐥𝐮𝐦𝐞, 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬. ✅ 𝐂𝐥𝐨𝐮𝐝 & 𝐌𝐋𝐎𝐩𝐬 — 𝐃𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐌𝐋 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐨𝐧 𝐀𝐖𝐒 | 𝐆𝐂𝐏 | 𝐀𝐳𝐮𝐫𝐞, 𝐥𝐞𝐯𝐞𝐫𝐚𝐠𝐢𝐧𝐠 𝐃𝐨𝐜𝐤𝐞𝐫, 𝐅𝐚𝐬𝐭𝐀𝐏𝐈, 𝐚𝐧𝐝 𝐂𝐈/𝐂𝐃 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐟𝐨𝐫 𝐬𝐞𝐚𝐦𝐥𝐞𝐬𝐬 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲. ✅ 𝐀𝐈 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 — 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐋𝐋𝐌𝐬, 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐍𝐋𝐏, 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐭𝐨 𝐩𝐮𝐬𝐡 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐞𝐫𝐚 𝐨𝐟 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞. ✅ 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 — 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐜𝐮𝐭𝐭𝐢𝐧𝐠-𝐞𝐝𝐠𝐞 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐢𝐧𝐠 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐚𝐧𝐝 𝐞𝐧𝐬𝐮𝐫𝐢𝐧𝐠 𝐞𝐯𝐞𝐫𝐲 𝐦𝐨𝐝𝐞𝐥 𝐞𝐯𝐨𝐥𝐯𝐞𝐬 𝐰𝐢𝐭𝐡 𝐧𝐞𝐰 𝐝𝐚𝐭𝐚 𝐚𝐧𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐭𝐫𝐞𝐧𝐝𝐬. 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 ✅𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐌𝐋 & 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬, 𝐫𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐚𝐧𝐝 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧/𝐫𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐮𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰, 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐚𝐧𝐝 𝐒𝐜𝐢𝐤𝐢𝐭-𝐥𝐞𝐚𝐫𝐧. ✅ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐄𝐓𝐋 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚 𝐩𝐫𝐞𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐟𝐨𝐫 𝐡𝐢𝐠𝐡-𝐯𝐨𝐥𝐮𝐦𝐞 𝐚𝐧𝐝 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬. 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 🏴󠁣󠁬󠁡󠁩󠁿 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐂𝐍𝐍𝐬, 𝐑𝐍𝐍𝐬, 𝐋𝐒𝐓𝐌𝐬, 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬, 𝐚𝐧𝐝 𝐕𝐢𝐬𝐢𝐨𝐧/𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬. 🏴󠁣󠁬󠁡󠁩󠁿 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 & 𝐍𝐋𝐏 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐢𝐦𝐚𝐠𝐞 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧, 𝐨𝐛𝐣𝐞𝐜𝐭 𝐝𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧, 𝐬𝐞𝐠𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧, 𝐭𝐞𝐱𝐭 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧, 𝐬𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬, 𝐚𝐧𝐝 𝐋𝐋𝐌 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧. 𝐋𝐋𝐌 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫-𝐁𝐚𝐬𝐞𝐝 𝐌𝐨𝐝𝐞𝐥𝐬 — 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐆𝐏𝐓, 𝐋𝐋𝐚𝐌𝐀, 𝐁𝐄𝐑𝐓, 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬, 𝐢𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐞𝐧𝐜𝐨𝐝𝐞𝐫, 𝐝𝐞𝐜𝐨𝐝𝐞𝐫, 𝐚𝐧𝐝 𝐞𝐧𝐜𝐨𝐝𝐞𝐫-𝐝𝐞𝐜𝐨𝐝𝐞𝐫 :

Machine Learning Engineer specializing in medical image analysis, deep learning, RAG pipelines, LLM development, generative AI and time series forecasting delivering production-ready AI systems built on real-world data. I help researchers, startups and enterprises turn complex data — medical images, documents, sensor signals and time series into reliable machine learning systems for detection, classification, prediction and intelligent automation. Every project I deliver is a working, documented system not a research prototype. Medical Image Analysis & Computer Vision I develop deep learning models for medical imaging and computer vision applications including image classification, object detection and semantic segmentation. Work covers MRI, CT, X-ray, whole slide image analysis, histopathology and EEG/ECG biosignal processing. Models: YOLOv8, UNet, ViT, EfficientNet, ResNet, Mask RCNN, SAM Frameworks: PyTorch, TensorFlow, OpenCV RAG Pipelines, LLM & Generative AI I build retrieval-augmented generation systems, AI agents and custom LLM chatbots for enterprise and research use. Work covers document Q&A, knowledge base search, LLM fine-tuning and AI workflow automation. Tools: LangChain, LlamaIndex, OpenAI GPT, LLaMA, Mistral, HuggingFace Vector DBs: ChromaDB, Pinecone, FAISS Time Series Forecasting & Anomaly Detection I build forecasting and anomaly detection models for finance, retail, IoT, energy and industrial domains. Work covers demand forecasting, predictive maintenance, multivariate time series and real-time anomaly detection. Models: LSTM, Transformer, Prophet, XGBoost, LightGBM Message me with your project — I will tell you exactly what is achievable and the best approach for your data.

With 7+ years of experience in AI/ML, I focus on building solutions that are not just technically sound but also practical and valuable in real-world scenarios. My work is driven by research, experimentation, and selecting the right technologies for each unique problem. 🔹 Where I Add Value I have strong hands-on experience in Computer Vision / Machine Vision, working on problems such as: * Object detection and recognition * Multi-camera tracking and digital twin systems * Face recognition and human pose estimation * Edge AI and real-time inference * Inspection systems and anomaly detection * OCR and text extraction * Data preparation including segmentation, augmentation, and synthesis 🔹 Machine Learning Expertise Depending on the problem, I apply a wide range of ML techniques: * Supervised Learning: Classification, Regression * Unsupervised Learning: Clustering, Dimensionality Reduction * Semi-supervised learning * Reinforcement learning 🔹 NLP & AI Systems Alongside vision, I’ve worked on intelligent systems involving: * GPT-based models (GPT-3, GPT-4) and LangChain workflows * Text summarization and content generation * Recommendation systems (feature-based, user-based, hybrid) * Sentence similarity and semantic analysis * Conversational AI and dialog systems * Speech processing (ASR, speech synthesis) * Machine translation 🔹 Deep Learning Applications I’ve applied deep learning across multiple real-world use cases: * Multi-camera tracking systems * Autonomous drones * Chatbots and service bots * Predictive analytics solutions I’ve also worked closely with startups and businesses to build MVPs and POCs, helping them validate ideas and move faster toward production. ✔️ Open to signing NDAs for confidential projects ✔️ Additional demos and project details available on request If you’re looking to build something in AI or want to explore a new idea, feel free to reach out happy to discuss and contribute. Best regards Disha

✔️ TOP RATED Freelancer specializing in Computer Vision and AI-based image processing systems. I enjoy building practical, production-ready solutions for real-world visual problems and would be glad to contribute to your project in a meaningful way. My core focus is on computer vision, especially tasks involving image understanding, detection, and extraction from complex or noisy inputs. I have strong experience working with: ✔️Image Classification & Fine-Grained Recognition (handling subtle visual differences) ✔️Object Detection (YOLO, SSD, Faster R-CNN, TFOD API) ✔️Image Segmentation (Mask R-CNN, semantic & instance segmentation) ✔️OCR & Text Extraction (structured documents, multi-format, noisy images) ✔️Image Preprocessing (denoising, deskewing, perspective correction, enhancement) ✔️OpenCV-based pipelines for real-time and production use ✔️Deep Learning frameworks: TensorFlow, Keras, PyTorch ✔️CNN Architectures: ResNet, VGG, Inception, EfficientNet ✔️Transfer Learning & Custom Model Training ✔️Synthetic Data Generation & Augmentation ✔️Vector Embeddings & Image Similarity Systems ✔️End-to-End CV Pipelines (data collection → training → deployment) Alongside this, I also have a solid foundation in: ✔️Machine Learning & Deep Learning ✔️Mathematics & Statistics (for model understanding and optimization) ✔️Python ecosystem (NumPy, Pandas, SciPy, etc.) ✔️API Development & Deployment(Docker, AWS, GCP) I hold a Bachelor’s degree in Computer Engineering and am currently pursuing a Master’s in AI, which helps me stay aligned with the latest advancements in the field. My approach is always to first understand the business problem and real-world constraints, and then design a solution that is accurate, scalable, and practical to use. I care deeply about delivering solutions that actually work for clients not just in theory, but in real-world conditions. Thanks & Regards, Ruchir