Hire the Best Artificial Intelligence Engineers

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.

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 am an AI engineer with 4 years of experience building and deploying production ready AI systems across computer vision, NLP, and generative AI. I have worked on everything clients need right now: fine tuning and training deep learning models, building RAG and GraphRAG pipelines, LLM powered applications, OCR and document extraction, real time face recognition and multi object tracking, classification systems, embedding pipelines, and end to end data workflows from raw input to deployed output. I also have experience with model optimization including distillation, pruning, and quantization for edge and cloud deployment. On the engineering side I am comfortable with FastAPI, PostgreSQL, pgvector, Python async, and cloud and GPU based deployments. I have built and shipped full stack AI products, not just models. I also lead a team of AI engineers, so I understand both deep technical execution and what it takes to deliver consistently on real projects. If you have an AI problem that needs to actually work in production, I can build it.

⭐Top Rated | 100% Job Success | 5-Star Execution ⭐ Let’s be real: Most "developers" here are just middle-men. When you hire me, you aren’t just getting a coder, you’re getting a technical partner who has built products for Dell, Cisco, and dozens of founders across every imaginable domain. I am a Gold Medalist Computer Science graduate, the Founder of OpenRox, and an AI Instructor who has taught 40+ sessions to the next generation of engineers and builders from all age groups. I don’t do "good enough." I build high-performance, scalable systems that actually make money. Doesn't matter if you need a custom AI Agent that thinks for itself, a complex Fintech platform with complex regulatory integrations, or a high-end mobile application, I deliver results. ⭕Why Founders work with me: - Full-Spectrum Mastery: From Embedded Systems (Arduino/Pi) to Game Engines (Unity/Unreal) and AI/ML (PyTorch/TensorFlow). - CEO Mindset: I run a tech agency. I understand ROI, deadlines, and why your business needs to scale. - Elite Pedigree: Top University Gold Medalist. I understand the deep math behind the AI, not just the "wrappers." - Instructor-Level Clarity: I teach this stuff. If I can explain AI to a 10-year-old, I can make your project's architecture crystal clear to you. ⭕ What I’ve Built Recently: - Custom AI Ecosystems: Engineered marketing automation platforms that handle content, email, and video generation autonomously. - Next-Gen V-Tubing: Built AI-driven virtual YouTubers using real-time scraping and OpenAI’s Agent API. - Revolutionary Fintech: Designed 1LINK-integrated financial tools for entrepreneurs with built-in AI advisors. - Creative AI: Systems that generate 3D logos, manga, and interactive stories from scratch. ⭕ My Technical Arsenal: - AI/ML: Custom Agents, NLP, TensorFlow, PyTorch, Scikit-learn, SpaCy. - Web & Mobile: React.js, Node.js, Python, Flutter Java, Swift, Kotlin, REST/GraphQL. - Games & Desktop: Unity, Unreal Engine, JavaFX, Electron, C#, C++. - Everything Else: Shopify, Liquid, WooCommerce, SQL, MongoDB, Firebase. If you want the best, let’s talk. If you want "cheap and slow," I’m not your guy. ✉️Click "Message" or "Invite" and let's turn your vision into a reality.

AI Architect & Senior ML Engineer with 10+ years of academic + industry experience building production-grade intelligence systems, LLM pipelines, and multimodal AI. I design and deploy end-to-end ML architectures, including LLM orchestration, timeseries modeling, graph ML, OCR pipelines, and automated image-processing systems. Trusted by enterprises for high-reliability AI, data privacy, and scalable ML infrastructure.

🚀 🥇 Expert-Vetted Talent | Principal AI/ML | GenAI, LLM, RAG, Fine-tuning, Cloud(Azure, AWS, GCP) | Healthcare & FinTech I transform complex business challenges into cutting-edge AI solutions. With 15+ years leading AI/ML initiatives and a Doctor of Philosophy in Machine Learning from Iowa State University, Master's in Computational Neuroscience from UC San Diego, I deliver production-ready GenAI systems that drive measurable ROI. ✅ What I Offer: • GenAI & LLM Solutions: Custom GPT fine-tuning, prompt engineering, multi-agent systems, RAG architectures • Production AI Systems: End-to-end ML pipelines, MLOps, model deployment at enterprise scale • Healthcare AI: Clinical trial automation, medical document generation, HIPAA-compliant solutions • AI Strategy & Architecture: Technical roadmapping, proof-of-concepts, AI transformation leadership • Full-Stack AI Development: Python, PyTorch, TensorFlow, AWS, GCP, Azure, Vector DBs, Kubernetes 🎯 Recent Achievements: • Built AI system processing 100K+ clinical trials for pharma enterprise, enabling intelligent Q&A and benchmarking • Developed GenAI platform generating 100+ page clinical trial protocols with 95% accuracy • Led 60+ engineer team delivering first commercial AI healthcare product at ResMed (NYSE: RMD) • Created $1M+ revenue AI products in first year at multiple startups • Secured $3.5M+ funding through strategic AI product development 💼 Industry Expertise: • Healthcare/Pharma: Clinical trials, EHR integration, medical AI, FDA-regulated software • FinTech: Real-time fraud detection, risk assessment, payment processing systems • Enterprise SaaS: Multi-tenant architectures, API development, scalable AI services • Retail/E-commerce: Recommendation engines, inventory optimization, customer analytics 🔧 Technical Stack: AI/ML: GPT-4/5, Claude, Llama, BERT, Transformers, Fine-tuning, RLHF, RAG, Vector Databases Languages: Python, JavaScript, TypeScript, Java, Ruby, Go, SQL Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, Scikit-learn, FastAPI Cloud/DevOps: AWS (SageMaker, Lambda, ECS), GCP (Vertex AI), Azure, Kubernetes, Docker Databases: PostgreSQL, MongoDB, Redis, Elasticsearch, Pinecone, Weaviate, ChromaDB Tools: MLflow, Weights & Biases, Git, CI/CD, Jupyter, Streamlit 📊 Quantifiable Impact: • 73% engagement increase for nonprofit youth chatbot with emotional intelligence • 94% accuracy in crisis detection for at-risk populations • 10X growth in subscriber base through AI-driven optimizations • 100+ pages of medical documents generated with regulatory compliance • $100K+/month revenue generated through ML-powered ad targeting 🎓 Credentials: • M.Sci. Computational Neuroscience - UC San Diego • IBM Certified: RAG and Agentic AI • Deep Learning Specialization - Coursera • Published researcher in AI/ML (Psychological Science, ICSE) • 4 provisional patents in AI/computer vision 🌟 What Sets Me Apart: Unlike typical developers, I combine deep technical expertise with business acumen from leading multiple successful startups. I don't just build models – I architect complete AI ecosystems that scale, comply with regulations, and deliver measurable business value. My neuroscience background provides unique insights into building truly intelligent systems that understand human behavior and needs. 📋 Services I Provide: • Custom LLM fine-tuning and deployment • RAG system architecture and implementation • Multi-agent AI system development • Healthcare AI and medical document automation • AI-powered data extraction and processing • Computer vision and image analysis solutions • Production ML pipeline development • AI strategy consulting and roadmapping • Technical due diligence for AI projects • Team mentoring and AI capability building 🤝 Working With Me: I pride myself on clear communication, translating complex AI concepts into actionable business strategies. Whether you need a production-ready AI system, strategic guidance, or technical leadership, I deliver solutions that exceed expectations. I'm available for both short-term projects and long-term engagements. Ready to transform your business with AI? Let's discuss how I can help you leverage the latest in GenAI, LLMs, and machine learning to achieve your goals. Keywords: Artificial Intelligence, Machine Learning, Deep Learning, GenAI, Generative AI, ChatGPT, GPT-4, GPT-5, Large Language Models, LLM, Fine-tuning, RAG, Retrieval Augmented Generation, RLHF, Vector Database, Embeddings, Transformers, NLP, Computer Vision, PyTorch, TensorFlow, Python, AWS, GCP, Azure, Healthcare AI, FinTech AI, MLOps, AI Architecture, Prompt Engineering, LangChain, Hugging Face