Mridul M.

AI/ML Developer | LLM, RAG, Computer Vision, Rust & Automation Expert

𝗣𝗥𝗢𝗙𝗘𝗦𝗦𝗜𝗢𝗡𝗔𝗟 𝗦𝗨𝗠𝗠𝗔𝗥𝗬 AI/ML Developer building production machine learning systems: LLM applications, RAG pipelines, NLP, and computer vision deployed against real-world problems. Over the past three years I have delivered 10–15 AI/ML engagements spanning conversational AI, custom ML pipelines, model deployment, and intelligent document processing. I pair this with a deep systems background in Rust and automation engineering, which lets me ship AI that is fast, reliable, and safe in production rather than confined to a notebook. My earlier work in distributed systems and blockchain informs how I build today: an emphasis on data integrity, verifiable pipelines, and secure system design—applied now to ML infrastructure and industrial automation rather than currency or trading. 𝗖𝗢𝗥𝗘 𝗘𝗫𝗣𝗘𝗥𝗧𝗜𝗦𝗘 o 𝗔𝗜/𝗠𝗟 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: LLM applications, RAG systems, fine-tuning, prompt engineering, LangChain o 𝗡𝗟𝗣: transformers, sentiment analysis, entity extraction, text classification o 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻: object detection, OCR, image classification, intelligent document processing o 𝗠𝗟𝗢𝗽𝘀: model deployment, vector databases, pipeline orchestration, monitoring o 𝗥𝘂𝘀𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: high-performance backends, concurrency, memory-safe system design, WebAssembly o 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 & 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀: RPA, ROS, industrial control integration, NVIDIA edge devices o 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸: React, Node.js, Python, FastAPI, microservices, cloud deployment 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗞𝗜𝗟𝗟𝗦 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: o LLMs: GPT-4 class models, Gemini, Llama 3, Mistral, Cohere o Frameworks: PyTorch, TensorFlow, scikit-learn, Hugging Face o NLP: spaCy, NLTK, transformers, RAG, semantic search o MLOps: MLflow, vector databases, model serving, deployment pipelines o Computer Vision: OpenCV, YOLO, object detection, OCR 𝗥𝘂𝘀𝘁 & 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: o Advanced Rust: async/await, concurrency, memory safety o Web: Actix-web, Axum, WebAssembly o Distributed systems: verifiable data pipelines, smart-contract integration (Anchor/Solidity) for provenance and supply-chain use cases o Performance: optimization, profiling, system programming 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻, 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 & 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹: o RPA: UiPath, Automation Anywhere, Blue Prism o Robotics: ROS1/ROS2, navigation, SLAM o Industrial: PLC integration, OPC UA/Modbus, edge AI on NVIDIA Jetson o Document Processing: OCR, intelligent extraction 𝗕𝗹𝗼𝗰𝗸𝗰𝗵𝗮𝗶𝗻 (𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 & 𝗣𝗿𝗼𝘃𝗲𝗻𝗮𝗻𝗰𝗲 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀): o NFC-linked physical asset provenance (NTAG 424 DNA, ERC-721) o Supply-chain traceability and authenticity verification o Smart contracts: Solidity, Rust (Anchor) for non-financial, asset-backed use cases 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗦𝘁𝗮𝗰𝗸: o Backend: Python, Node.js, FastAPI, GraphQL o Frontend: React, Vue.js, TypeScript o Databases: PostgreSQL, MongoDB, Redis, pgvector o Cloud: AWS, GCP, Docker, Kubernetes, CI/CD 𝗦𝗘𝗥𝗩𝗜𝗖𝗘 𝗢𝗙𝗙𝗘𝗥𝗜𝗡𝗚𝗦 o 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: LLM/RAG applications, custom ML pipelines, NLP, computer vision, conversational AI o 𝗔𝗜 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗶𝗮𝗴𝗻𝗼𝘀𝘁𝗶𝗰𝘀 & 𝗔𝘂𝗱𝗶𝘁: reliability review, failure analysis, and architecture audit for ML systems o 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: RPA, document processing, workflow optimization o 𝗥𝘂𝘀𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: high-performance backends, WebAssembly, systems programming o 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: end-to-end development, API integration, cloud deployment 𝗣𝗥𝗢𝗙𝗘𝗦𝗦𝗜𝗢𝗡𝗔𝗟 𝗤𝗨𝗔𝗟𝗜𝗧𝗜𝗘𝗦 o Strong analytical and problem-solving capabilities o Clear technical communication and client collaboration o Security-first, reliability-first development approach o Comprehensive testing and quality assurance 𝗖𝗔𝗥𝗘𝗘𝗥 𝗙𝗢𝗖𝗨𝗦 Building and auditing production AI/ML systems—LLM applications, computer vision, and intelligent automation—backed by a systems engineering foundation that keeps them fast, verifiable, and safe.