Hire the Best Artificial Intelligence Engineers

AI expert. PhD student in AI/ML. Anthropic certified. I build Claude native: agents, RAG, and automations that ship. 5 years in one domain. 30+ businesses delivered, I also create content on YouTube, Medium and X, because if you do not teach it, you do not really know it. Most "AI engineers" are 6 months in and Googling on your budget. I read the papers the week they drop and ship the patterns the month after. That is what you are paying for. What I build: - RAG chatbots and agents over your docs, PDFs, Notion, knowledge base - LLM fine-tuning on your domain data - Workflow automations replacing 40 to 80 percent of manual ops - Solution architecture before you commit to the wrong stack - Recovery work on stalled AI projects Stack: Claude, LangChain, Azure AI, Hugging Face, Pinecone, Weaviate, Neo4j Graph RAG, Python, Next.js. Response under 4 hours. Weekly Loom demos. Fixed scope after a free 20 minute call. 100 percent Job Success, Top Rated. Send the project. Same day reply with a plan, a question, or an honest pass.

Healthcare AI built by an engineer who knows buyers are right to filter out generalists. Medical imaging on DICOM, clinical NLP that handles negation and hedging, HIPAA-aware PHI pipelines, patient-facing apps that respect privacy for hospitals, radiology centres, pharma R&D, CROs, medical device makers, health-tech teams. I work with the Brainy Neurals team as the healthcare-AI engineer. My focus sits between "we have clinical data" and "validated AI helping clinicians" model design, PHI handling under your BAAs, on-prem vs cloud, validation against radiologist ground truth, shipping into EHR or device workflow. WHAT I BUILD / IN HEALTHCARE Medical imaging AI — DICOM ingestion, de-identification per Safe Harbor, organ and lesion segmentation on CT and MRI, abnormality detection, NIfTI and ITK pipelines, 3D Slicer. Built on MONAI, nnU-Net, TotalSegmentator, RadImageNet, validated against radiologist consensus. Clinical NLP and document AI note summarisation, ICD and SNOMED mapping, negation and hedging, family-vs-patient history disambiguation, medication extraction, lab-report parsing, prescription OCR. The grammar of clinical text is its own thing; I treat it accordingly. Pharma and clinical research clinical protocol to eCRF extraction (demographics, vitals, inclusion-exclusion, study-arm), systematic review using RoB2, GRADE, PRISMA, citation validation, batch record digitisation, evidence assembly. Patient-facing apps GI symptom-trackers with AI food and lifestyle recommendations, diabetic and gut-condition dish-suggestion, telehealth onboarding, chronic-care intake, mental-health support. Flutter or React Native fronts, FastAPI backends. Hospital workflow AI appointment automation, triage, hand-hygiene monitoring, fall-detection in wards (pose-based, no face recognition), bed-occupancy. THE STACK / FOR MEDICAL & PHARMA Imaging: MONAI, DICOM, NIfTI, ITK, 3D Slicer, nnU-Net, TotalSegmentator, RadImageNet, modality fusion. Clinical NLP and docs: Docling for medical PDFs, DocTR and TR-OCR for prescription and lab OCR, GPT-4o multimodal for complex layouts, Claude and Gemini for clinical reasoning, regex and Pydantic validation, NegEx-style negation with LLM verification. Knowledge: Neo4j for clinical knowledge graphs (drug-drug interaction, condition-symptom, contraindications). pgvector or Qdrant for medical literature. RAG over institutional protocols, authoritative sources only. Infrastructure: FHIR and HL7 v2 with EHRs, OMOP CDM for research, FastAPI for clinical APIs, Flutter and React Native for patient apps, AWS and Azure inside client BAAs, on-prem Ollama and vLLM where data cannot leave. WHO I BUILD FOR Hospitals and clinics radiology AI, patient-flow analytics, EHR decision support, ward-safety. Radiology centres, DICOM pipelines, organ and lesion segmentation, second-read AI, reporting integration. Pharma R&D and CROs clinical protocol extraction, systematic review, eCRF generation, evidence assembly. Medical device (pre-clearance) model prototyping, validation harnesses, dataset curation. I do not claim FDA-cleared deliverables; I build the substrate that goes through your regulatory team. Telehealth and health-tech patient intake, AI triage, multilingual symptom-checker. Specialty practices dental, dermatology, gastroenterology, oncology, mental health. Specialty-tuned models on small datasets. Health insurance claim review, prior-auth triage, appeals support, evidence extraction. HOW I WORK / WITH HEALTHCARE BUYERS Discovery is a 30-minute call: data sources, clinical workflow, compliance posture (HIPAA, GDPR, local). By the end I tell you whether the use case is feasible, validation plan, where ground truth comes from, how PHI flows. If it touches a regulated device pathway, I tell you what is in scope for me and what your regulatory team owns. Pricing is fixed-scope per milestone feasibility, dataset and PHI design, model build, validation, integration handoff. Hourly only for maintenance after deploy. THE BRAINY NEURALS BACKING I work with the Brainy Neurals team 15 AI engineers, NVIDIA Inception Partner, AWS Activate, Microsoft for Startups. When a project needs ward-monitoring cameras, edge deployment on hospital hardware, RAG over clinical docs, or workflow automation around the AI, that capacity sits with the team I bring them in cleanly, you do not manage multiple vendors. For pure healthcare model and clinical-NLP work I lead end to end myself. LET'S TALK / IF You are inside healthcare or pharma, you have a clinical workflow AI can genuinely help with, you understand the validation and compliance work this requires, and you want a senior engineer who has built medical imaging, clinical NLP, and patient-facing apps before not a generalist learning HIPAA on your project. Tell me your data, workflow, compliance. I reply within 24 hours with feasibility, validation approach, milestones.

I primarily work on four types of projects: 1) Crafting your AI Strategy Expand your business vision with the latest tools and frameworks. Teach me about your industry, and I'll steer your AI journey from discovery through deployment—identifying opportunities, crafting your roadmap, and shaping a data-driven strategy that delivers measurable impact. 2) Automation and Intelligent Workflows Transform time-sensitive, repetitive tasks into streamlined, AI-powered workflows—from lead validation and customer onboarding to compiling accurate, visually compelling reports and advanced analytics. I help boost efficiency, reduce manual effort, and scale your operations. 3) Conversational bots and Multi-Agent Systems Engage users and help employees with text and audio based conversations. Whether for customer service, data scientists on top of internal DBs and training material, or compliance-based communication, our solutions act autonomously and collaborate seamlessly to get things done. 4) AI-Assisted Full Stack Development Our team is trained to use AI judiciously during every stage of development. Vibe coding can go horribly wrong when in the hands of the uninitiated, but when you combine tools like Cursor with our engineering expertise, you get reliable new products and services faster than has ever been possible. My portfolio has more examples, but in short, if you're looking to build specialized agents to perform enterprise-ready tasks, you'd be hard-pressed to find a more qualified developer anywhere on Upwork. I'll be applying as an organization - krazimo (krazimo.com), so you'll get two world-class engineers (Mridul and I) working on your project, as well as a number of junior engineers to perform the smaller engineering tasks. You'll have full transparency into who's doing what, and our junior engineers work for approximately 2/3 our hourly rate. Here's a little about my 11 years of experience. Google (2019-2025) I spent six years as a senior software engineer at Google. My two major projects currently were Admin AI Assistant: I'm worked as an LLM specialist on building a RAG solution to improve Google's customer service in our workspace Admin Console. Gemini Reporting: Led a team of 10 people in building a large scale pipeline that can handle high QPS events on Gemini usage and report on value and RoI for our Gemini Product in Google Workspace. Apart from these, I have designed, implemented and shipped many technically complex products at Google. They often involved coordinating efforts among large teams and always required me to adhere to the highest engineering standards. I hope I can bring this expertise to your company. NLP Engineer (2016-2019) Cofounded, Headed AI and built the prototype and MVP for Butter.ai, which raised $3M in seed funding and was eventually acquired by Box. Worked on sentiment analysis problems for psychiatric chat centers (analysis user messages to flag dangerous situations) Worked on text extraction and question answering problems for a company that helped health insurance providers answer complex questions related to a customer's coverage. Mobile Engineer (2013-2015) Worked on a number of apps for clients - including building the cleartax.in android application. Worked at IBM as a software engineer on a MDM product that involved core android development (very low level control of services and permissions). At the moment, this process is more about exploring the space and seeing what people are looking for in the world of AI, outside massive AI-centric companies like Google (my hourly rate is actually below my current salary, so you're getting a pretty great deal while I perform this exploration)!

I'm an 🥇Expert-Vetted, 𝐒𝐞𝐧𝐢𝐨𝐫 𝐀𝐈/𝐌𝐋 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 with 𝟏𝟎+ 𝐲𝐞𝐚𝐫𝐬 𝐨𝐟 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 shipping machine learning systems at Fortune 10 companies including Optum, Target, General Mills, and Medtronic. I hold a Ph.D. in Biomedical Engineering and an M.S. in Computer Science (4.0 GPA), combining deep research expertise with real-world engineering skills. My specialty is turning complex AI/ML challenges into deployed solutions that drive measurable business results—especially in healthcare, finance, education, and e-commerce. Right now, I lead AI initiatives that process millions of medical claims. ⚡ 𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃 - 𝐋𝐋𝐌 & 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 • RAG-based chatbots and Q&A systems using OpenAI, LangChain, and vector databases • Custom LLM pipelines for document processing, summarization, and extraction • Foundation models and domain-specific embeddings using Transformer architectures • Prompt engineering and LLM fine-tuning for specialized use cases - 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 • End-to-end ML pipelines: data processing → model training → deployment → monitoring • Deep learning models (CNNs, RNNs, Transformers) for classification, prediction, and generation • Gradient boosting models (XGBoost, CatBoost, LightGBM) for tabular data • Time-series forecasting, anomaly detection, and predictive analytics - 𝐍𝐋𝐏 & 𝐓𝐞𝐱𝐭 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 • Text classification, named entity recognition, and sentiment analysis • Semantic search and document similarity systems • Neural text embeddings for downstream ML applications - 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐫 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 & 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 • Collaborative filtering and content-based recommendations • Neural embedding approaches (item2vec, hierarchical embeddings) • Personalization engines for e-commerce, content, and promotions 🛠️ 𝐓𝐄𝐂𝐇𝐍𝐈𝐂𝐀𝐋 𝐒𝐓𝐀𝐂𝐊 • Languages: Python, SQL, R, C++, Bash • LLM/GenAI: OpenAI API, LangChain, Hugging Face Transformers, RAG • ML/DL: PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, CatBoost • NLP: spaCy, NLTK, Gensim, sentence-transformers • Cloud: AWS, GCP, Azure • Big Data: Spark, Hive, Hadoop, Dask • Data: Pandas, NumPy, SQL databases, vector databases (Pinecone, ChromaDB) 🏆 𝐏𝐑𝐎𝐕𝐄𝐍 𝐑𝐄𝐒𝐔𝐋𝐓𝐒 ✅ 𝐔𝐧𝐢𝐭𝐞𝐝𝐇𝐞𝐚𝐥𝐭𝐡 𝐆𝐫𝐨𝐮𝐩 ➤ Leading ML system development that automates claim review processes, reducing manual workload ➤ Built foundation model for medical claims embeddings using Transformer architecture and multi-instance learning ➤ Developed RAG-based chatbot using GPT-3.5 with call center transcripts as knowledge base ➤ Created attention-based deep learning model for personalized patient care-path prediction (patent filed) ➤ Shipped CatBoost model for automated claim adjudication ✅ 𝐓𝐚𝐫𝐠𝐞𝐭 ➤ Implemented item2vec neural embeddings powering personalization for all Target guests ➤ Developed hierarchical item2vec algorithm incorporating product taxonomy in production ➤ Built recommendation diversification algorithms improving customer engagement ✅ 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐌𝐢𝐥𝐥𝐬 ➤ Deployed ARIMA and regression forecasting models on GCP for all North American products ➤ Created commodity price forecasting system scaled to 20+ commodities ➤ Built search algorithm for historical crop year similarity analysis in production ✅ 𝐌𝐞𝐝𝐭𝐫𝐨𝐧𝐢𝐜 & 𝐒𝐭𝐚𝐫𝐤𝐞𝐲 ➤ Developed ML algorithms for FDA-cleared implantable medical devices ➤ Built seizure detection system using spectral features from neural signals ➤ Created fall detection and respiratory monitoring algorithms using sensor fusion ➤ 6 patents granted/pending for neural signal processing innovations 🎓 𝐂𝐑𝐄𝐃𝐄𝐍𝐓𝐈𝐀𝐋𝐒 • Ph.D. Biomedical Engineering (Neural Engineering) — University of Minnesota • M.S. Computer Science (Data Science) — University of Illinois Urbana-Champaign, 4.0 GPA • B.S. Bioengineering — UC Berkeley • 6 Patents in AI/ML and medical device algorithms • 15+ Publications in peer-reviewed journals and conferences • Certifications: Pretraining LLMs, Generative AI with LLMs, Deep Learning for Healthcare, plus 30+ specialized courses 🌍 𝐈𝐃𝐄𝐀𝐋 𝐏𝐑𝐎𝐉𝐄𝐂𝐓𝐒 ✔ LLM/RAG application development (chatbots, Q&A systems, document processing) ✔ Healthcare AI and clinical data science ✔ Custom ML model development and deployment on AWS/GCP ✔ NLP pipelines and text analytics systems ✔ Recommender systems and personalization engines ✔ Time-series forecasting and predictive modeling ✔ ML architecture consulting and technical advisory I've led teams of data scientists and engineers, mentored junior practitioners, and collaborated with business stakeholders at every level. I understand that great technical work means nothing if it doesn't solve the actual business problem. Ready to discuss your project?

Most Machine Vision projects fail between the prototype and production. I've shipped 54+ that didn't. ⚙️YOLO Detection | Pose Estimation | Object Tracking | AI Agents | LLM Integration Sports & Fitness AI | CCTV & Surveillance AI | Retail AI | Healthcare AI You have a working concept... or a clear problem involving cameras, video, or image data. The challenge is making it fast, accurate, and stable under real-world conditions. Wrong framework choices. Inference too slow for live video. Models that break the moment lighting, angle, or environment changes. And systems that detect things but can't reason about them or act on them autonomously. That's exactly where most builds stall. I design and build real-time computer vision pipelines that go all the way... from model training to live deployment... and increasingly, from visual perception to autonomous AI agents that understand, decide, and narrate. LLM APIs (OpenAI, GPT-4o, Gemini, Claude) | AWS (EC2, S3, Lambda) | Azure Cloud Services | MLOps & API Integration | Model Deployment & Scaling While most CV engineers stop at training the model, I go further: → High-speed inference optimization using TensorRT, ONNX, OpenVINO, FP16/INT8 (up to 5× faster) → LLM agents integrated with vision pipelines for alerts, reasoning, and automation → Mobile AI deployment using Core ML (iOS) and TFLite (Android) with 10+ shipped apps → Edge AI deployment on Jetson, OpenVINO, CUDA, and embedded systems → End-to-end pipelines: data → training → optimization → real-time deployment Key Accomplishments: ⭐ $5M+ revenue from AI solutions ⭐ 100+ computer vision systems delivered ⭐ Built and launched 2 SaaS products ⭐ Real-time sports AI (7+ sports, 15+ teams) ⭐ 10+ mobile AI apps (iOS Core ML, Android TFLite) ⭐ Production AI for surveillance, industrial & safety use cases ⭐ Medical imaging AI deployed in 5+ hospitals ⭐ Up to 5× faster inference (ONNX, TensorRT, FP16/INT8) ⭐ Large-scale tracking & re-ID (1M+ labeled data) ⭐ Agentic AI systems for autonomous decision-making If you have read this far, please note that I appreciate you taking the time to learn about me. Personally, it’s been an amazing journey and knowledge exercise to get to this level of competence in AI and software development. Domain Expertise: ✅ athlete tracking | shot detection | scoring | drill analysis | pose estimation ✅ defect inspection | PPE compliance | staff monitoring | meter reading | quality control ✅ ANPR | crowd monitoring | people counting | intrusion detection | perimeter security ✅ tumor detection | ultrasound | X-ray/CT analysis | lesion segmentation | medical imaging ✅ aerial monitoring | traffic flow | license plate recognition | vehicle & accident detection ✅ customer analytics | receipt extraction | shelf monitoring | inventory tracking Tech Stack: YOLOv5–YOLOv8–YOLOv11, Detectron2, MMDetection, DeepSORT, StrongSORT, MediaPipe, OpenPose, Pose Estimation, Action Recognition, Segmentation (semantic & instance), OCR, anomaly detection, object tracking, PyTorch, TensorFlow, TFLite, Core ML, OpenCV, FastAPI, Flask, ONNX, TensorRT, OpenVINO, CUDA, AWS, Azure, GCP, edge AI, mobile AI, real-time inference, video analytics, AI automation, LLM integration (GPT-4o, Claude, Gemini, Groq), LangChain, LangGraph, CrewAI, RAG systems. 💬 If your project involves cameras, video, or images... and you need it fast, accurate, fully deployed, and intelligent enough to reason and act autonomously... I am the engineer you are looking for.

🤖𝐈𝐟 𝐦𝐲 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐝𝐨𝐞𝐬𝐧’𝐭 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐲𝐨𝐮𝐫 𝐚𝐠𝐫𝐞𝐞𝐝 𝐦𝐞𝐭𝐫𝐢𝐜𝐬, 𝐲𝐨𝐮 𝐝𝐞𝐬𝐞𝐫𝐯𝐞 𝟏𝟎𝟎% 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐦𝐨𝐧𝐞𝐲 𝐛𝐚𝐜𝐤. Most businesses hire AI developers to build what they ask for. That's the problem. I don't just build what clients request - I figure out what they actually need first. Usually what they think they need isn't the highest-ROI opportunity. AI-powered solutions delivering production-ready systems measurable ROI and high-impact results - not just prototypes. Work spans finance, healthcare, e-commerce, construction, academia and web platforms, often unlocking $100K–$300K in annual savings 𝐍𝐄𝐗𝐓 𝐒𝐓𝐄𝐏𝐒:- Send me a message with your project problem, budget & timeline. I’ll reply within 24 hours to confirm if I’m the right fit. What Is Built / How Problems Are Solved with AI: ▶️ Multi-Agent AI Systems (LangGraph, LangChain) ▶️ Custom RAG Pipelines (OpenSearch, Pinecone, Supabase) ▶️ Voice AI (VAPI, ElevenLabs, LiveKit) ▶️ Sales & Support Automation (chat + voice) ▶️ Process Automation (n8n, Make, Zapier) ▶️ Full-Stack Development (Node.js, Python, React, Next.js, React Native) ▶️ Dashboards, forecasting models, ETL pipelines ▶️ Chatbots for WhatsApp, Telegram, SMS (via Twilio) My Portfolio Includes: ✔️ Generative AI development: GPT-4o, Claude, Mistral, Llama, Hugging Face, LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, Qdrant, Stable Diffusion, Flux 1.1, Ideogram, Lora, n8n, Agentic AI, CrewAI, BabyAGI, AutGen, DeepSeek, Prompt Engineering ✔️ Cost & performance optimization of AI applications ✔️ Time series forecasting models ✔️ ETL & data automation (Airtable, Webflow, Make) ✔️ AI Web development (Django, Flask, Dash with ML models) ✔️ Payment Gateway Integration ✔️ Dashboard development (Plotly Dash, PowerBI, Excel, Looker) ✔️ Data Analytics & Reporting ✔️ Translating business problems to technical teams ✔️ Geospatial Mapping ✔️ Chatbot integration (WhatsApp, Telegram, SMS via Twilio) ✔️ API development & integration ✔️ Research Publications Tech Stack/ Expertise: ⏺️ Python Libraries: Scikit Learn, Pandas, Numpy, Plotly, Tensorflow, Facebook Prophet, Spacy, NLTK, GeoPandas, OpenAi, LangChain, HuggingFace, Matplotlib, Seaborn ⏺️ Web Development: Dash, Django, Flask, FastAPI, Docker, MySQL, MS SQL, Pinecone, HTML5, CSS3, JavaScript ⏺️ MS Office: Excel (Advanced), PowerPoint (Advanced), Word (Advanced), Project ⏺️ Data Visualization / BI: Power BI, Looker, Tableau ⏺️ Front-end Tools: HTML5, CSS3, JavaScript ⏺️ Big Data Tools: PySpark, Hadoop ⏺️ Web-Scraping: Beautiful Soup, Scrapy, Selenium, Playwright ⏺️ Version Control: Git ⏺️ ERP Tools: SAP, Hysabat ⏺️ Cloud Technology: GCP, AWS, Azure, Digital Ocean Why Clients Hire: ⭐ Guidance on what NOT to build (most consultants won’t do this) ⭐ 5.0 rating ⭐ Production systems with metrics, logs, and clean handoffs ⭐ Coordinate senior engineers across ML, data, and cloud ⭐ Clear communication and global availability Let’s build AI solutions that actually work. #AIAgentDevelopment #DataAnalysis #DataEngineering #CloudComputing #PredictiveModeling #MLOps #ImageProcessing #AIChatbot #Python #OpenAIAPI #VectorDatabase #ArtificialIntelligence #RAG #LangChain #Pinecone #MultimodalAI #ProductionDeployment #Deep Learning #Artificial Neural Network #Chatbot Development #Computer Vision #Natural Language Processing #Machine Learning #Artificial Intelligence Ethics #Artificial Intelligence #Chatbot #Machine Learning #Deep Neural Network #Data Visualization #Data Analysis #Information Analysis #Data Science #Data Cleaning #Prompt Engineering #Generative AI #Large Language Model #Granite