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Expert-Vetted Top 1% on Upwork | Top 10 Machine Learning Agency on Upwork | 7+ Years in Production AI | Sports, Industrial, Satellite, Healthcare I'm a Computer Vision Engineer and Machine Learning Engineer with 7+ years delivering production-grade AI systems. Upwork has Expert-Vetted me as a Top 1% specialist in this niche, and our team is ranked among the Top 10 Machine Learning agencies on Upwork. I work with product teams and startups across sports analytics, industrial inspection, satellite and aerial imagery, access control, healthcare, and generative AI — any domain where visual data needs to become reliable, actionable output running in production. As a Computer Vision Engineer, my core work covers object detection, multi-object tracking, pose estimation, image segmentation, image processing, and real-time video analysis. I build end-to-end pipelines in Python using OpenCV, PyTorch, TensorFlow, and Keras, from dataset preparation and model training through TensorRT optimization and Docker deployment on cloud or NVIDIA Jetson edge hardware. I use C++ for performance-critical components where Python latency is a bottleneck. The domains where computer vision engineer experience creates the most value: sports analytics (player tracking, performance metrics, automated statistics from broadcast video), industrial inspection (defect detection and quality control on production lines), satellite and aerial imagery (object detection and segmentation for infrastructure analysis), access control and security (vehicle identification, multi-camera real-time monitoring), and healthcare and biomechanics (pose analysis, body measurement, and biomedical signal processing connected to AI coaching backends). As a Machine Learning Engineer and Data Scientist, I also build systems for structured and time-series data: demand forecasting, anomaly detection, biomedical signal analysis, and structural health monitoring. My data scientist workflow covers scikit-learn, pandas, NumPy, and SciPy alongside deep learning frameworks, with experiment tracking and evaluation metrics to ensure models perform consistently in production. When projects require generative AI or LLM components, I deliver RAG pipelines with LangChain and vector databases, synthetic dataset generation tools, and document processing systems using the Gemini API. Regardless of domain, the computer vision engineer approach stays the same: combine OpenCV-based preprocessing with deep learning inference into a scalable, testable pipeline that holds up under real-world conditions — variable lighting, occlusion, low resolution, multi-camera setups, and edge hardware constraints. I work with YOLO-family models, ByteTrack and DeepSORT for tracking, MediaPipe and MMPose for pose estimation, TensorRT and ONNX for inference optimization, and FastAPI with Docker for production deployment. I work with a specialized team that includes a computer vision PhD, deep learning researchers, and mathematical optimization specialists. This lets me scope complex systems, split parallel workstreams, and deliver a full Computer Vision Engineer engagement faster than a solo contributor could. Clients typically work with me when they need: - a Computer Vision Engineer to build detection, tracking, or segmentation systems from scratch - a Machine Learning Engineer to productionize a research model and meet latency requirements - a Data Scientist who can go from raw data to a deployable model end-to-end - an AI engineer to integrate LLM or generative components into an existing backend - real-time or edge inference optimized for NVIDIA Jetson or mobile deployment - a Python developer who understands both the AI pipeline and the surrounding system architecture If you need a Computer Vision Engineer with the full stack from dataset to deployed API, let's talk. Main stack: Python, OpenCV, PyTorch, TensorFlow, Keras, YOLO, ByteTrack, MediaPipe, MMPose, CoreML, TFLite, TensorRT, ONNX, scikit-learn, FastAPI, Docker, PostgreSQL, C++, NumPy, pandas, SciPy.

🚀 Top 1%, Expert-Vetted, AI Engineer 🚀 𝐒𝐞𝐧𝐢𝐨𝐫 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐰𝐢𝐭𝐡 𝟖+ 𝐲𝐞𝐚𝐫𝐬 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐜𝐮𝐭 𝐜𝐨𝐬𝐭𝐬, 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐚𝐧𝐝 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐑𝐎𝐈. I have helped startups and enterprises across healthcare, fintech, ecommerce, and SaaS ship intelligent AI products that scale from day one. I handle everything end to end, from idea to deployed production-grade AI. Have a great idea but 𝒏𝒐𝒕 𝒔𝒖𝒓𝒆 𝒘𝒉𝒆𝒓𝒆 𝒕𝒐 𝒔𝒕𝒂𝒓𝒕? Send me a DM and we will arrange a 𝟒𝟎-𝐦𝐢𝐧 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐭𝐢𝐨𝐧 📞. ★ 𝐖𝐡𝐚𝐭 𝐈 𝐃𝐞𝐥𝐢𝐯𝐞𝐫 → 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬: Autonomous multi-agent systems using LangGraph, CrewAI, AutoGen, and MCP that plan, reason, and execute across APIs, CRMs, and SaaS tools without human intervention. → 𝐑𝐀𝐆 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 & 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: Production RAG pipelines with hybrid search, contextual memory and hallucination mitigation using LlamaIndex, LangChain, Pinecone, Qdrant, Weaviate, and pgvector. → 𝐀𝐈 𝐂𝐡𝐚𝐭𝐛𝐨𝐭𝐬 & 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: Custom AI chatbots and inbound/outbound voice agents for customer support, lead qualification and appointment booking via web, WhatsApp, and phone using GPT-4o, Claude, Whisper, VAPI, and Retell AI. → 𝐋𝐋𝐌 𝐅𝐢𝐧𝐞-𝐓𝐮𝐧𝐢𝐧𝐠 & 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈: Domain-specific fine-tuning using LoRA, QLoRA, RLHF and DPO on OpenAI, Claude, Mistral, LLaMA 3, and DeepSeek for production-ready specialized model behavior. → 𝐀𝐈 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: AI integration into your CRMs, ERPs and databases via n8n, Make, and Zapier with OCR pipelines, web scraping, ETL automation and event-driven API orchestration. → 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 & 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐀𝐈: Object detection (YOLOv8), image classification, facial analytics and intelligent OCR for structured data extraction from PDFs and scanned documents. → 𝐌𝐋𝐎𝐩𝐬, 𝐂𝐥𝐨𝐮𝐝 & 𝐀𝐈 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: Scalable model deployment on AWS Bedrock, GCP Vertex AI and Azure with Docker, Kubernetes, CI/CD, LangSmith observability and token cost optimization. ★ 𝐍𝐨𝐭𝐚𝐛𝐥𝐞 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 ✔ 𝐀𝐈 𝐂𝐚𝐥𝐥 𝐒𝐜𝐨𝐫𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦: 90% faster evaluations, $140K+ saved in year one, 3x agent performance visibility across 10K+ calls/month. ✔ 𝐃𝐨𝐜-𝐀𝐈 𝐎𝐂𝐑 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞: 94% less manual data entry, $110K saved/yr, 50K+ documents processed/month at 99% accuracy. ✔ 𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐑𝐞𝐜𝐨𝐫𝐝 𝐄𝐱𝐭𝐫𝐚𝐜𝐭𝐢𝐨𝐧 (𝐅𝐢𝐧𝐞-𝐓𝐮𝐧𝐞𝐝 𝐋𝐋𝐌): 98% less processing time, $160K saved/yr, zero compliance errors in production. ✔ 𝐋𝐢𝐜𝐞𝐧𝐬𝐞 𝐏𝐥𝐚𝐭𝐞 𝐑𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧 (𝐘𝐎𝐋𝐎𝐯𝟖): 96% fewer manual checks, $85K saved/yr, real-time detection at 60fps. ✔ 𝐑𝐀𝐆 𝐑𝐞𝐩𝐨𝐫𝐭 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦: 98% faster prep, $200K saved/yr, zero hallucination rate across 5K+ reports. ✔ 𝐔𝐆𝐂 𝐕𝐢𝐝𝐞𝐨 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 (𝐧𝟖𝐧 + 𝐆𝐞𝐧𝐀𝐈): 90% production time cut, $120K saved/yr, 500+ videos/month fully automated. ✔ 𝐒𝐭𝐚𝐛𝐥𝐞 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧 𝐋𝐨𝐑𝐀 𝐅𝐢𝐧𝐞-𝐓𝐮𝐧𝐢𝐧𝐠: 95% lower compute cost, $90K saved per model cycle, brand-consistent image generation at scale. ★ 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐌𝐞 ✔ 𝐅𝐢𝐧𝐥𝐚𝐧𝐝, 𝐄𝐔 𝐁𝐚𝐬𝐞𝐝: EU timezone, GDPR-compliant development, and European enterprise communication standards with zero barriers. ✔ 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐓𝐞𝐚𝐦: I work alongside a dedicated team of AI engineers, ML specialists, and full-stack developers giving you agency-level capacity with direct senior ownership on every project. ✔ 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐅𝐢𝐫𝐬𝐭: I build AI that handles real traffic, edge cases, and failures gracefully, not demos that break under pressure. ✔ 𝐑𝐎𝐈-𝐃𝐫𝐢𝐯𝐞𝐧: Feasibility, scalability, and cost impact assessed before a single line of code is written. ✔ 𝐓𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐭 & 𝐑𝐞𝐥𝐢𝐚𝐛𝐥𝐞: Honest timelines, clear progress updates, and full post-launch support every time. 𝐋𝐞𝐭'𝐬 𝐁𝐮𝐢𝐥𝐝: Send me your project and I will give you a straight, honest assessment of what is feasible, what it will take, and how to build it the right way.

🎯 I turn raw ideas into AI-powered products investors back & users love • Ex-Google & NGINX engineer, • Top-1% Upwork "Expert-Vetted" freelancer, • AI / full-stack architect with 100 + shipped products powering 1 M+ monthly users and helping founders raise $30 M+. 🚀 RESULTS * SaaS platforms & mobile apps that closed $50 M+ in VC rounds * AI agents & RAG chatbots saving 1000s of staff hours monthly across law, procurement, healthcare & finance * Digital products delivering 1 M+ monthly active users and 7-figure ARR growth 🤝 WHY FOUNDERS HIRE ME * Investor-ready builds - Planning to raise? I understand what it takes to impress VCs - from demo-day-ready UX to scalable architecture that holds up under due diligence. * Battle-tested delivery – 10 + years of experience with Google, NGINX/F5 & high-growth startups * Speed without chaos – Lean scope, fast reliable launches, clear milestones, weekly demos, * no-surprise invoices. * Built-in AI edge – Ship smarter products faster with AI agents, RAG, fine-tuned LLMs, and vector search - without hiring a separate ML team. * True partnership – Aligned with your business goals: product strategy, UX polish, post-launch optimization, and VC + go-to-market support (AI-driven SEO, ChatGPT/Google/Bing indexing, ads, directories) – not just coding. 🗺️ MY PROVEN PROCESS TO BUILD SAAS 1. Discovery → AI opportunity mapping & success metrics (BRD, wireframes, technical architecture) 2. Clickable Prototype → Investor-ready demo in 7-14 days 3. Incremental Build → Weekly value drops with real-time staging links 4. Launch & Iterate → Observability, A/B tests, cost & latency tuning 📞 NEXT STEP Ready to turn your vision into reality? Invite me to your job or drop a message for a free strategy call. Let's build something investors fund and users rave about -together. 🔧 TECH STACK React / Next.js • React Native & Flutter • Python, FastAPI • Prisma & tRPC • PostgreSQL, Supabase • AWS Bedrock, GCP Vertex • OpenAI GPT, Anthropic Claude • LangChain, LangGraph, LlamaIndex • Pinecone, Weaviate • WebGPU & WASM • MCP, A2A, n8n, Clawdbot, Make . com automations • Docker & Kubernetes

Do you have an AI vision that needs to become a real, working product? I don't just build models; I engineer complete, scalable solutions that turn data into actionable insights and automation. For over five years, I've specialized in bridging the gap between cutting-edge Artificial Intelligence (AI) research and robust software that delivers real-world value. My core expertise lies in computer vision and machine learning, but my skill set is full-stack. This means I can own your project from the initial data pipeline, through model training and optimization, all the way to deploying a polished desktop application or a secure enterprise API. I thrive on building tools that work seamlessly for end-users, whether it's a retail manager, a traffic controller, or a sports coach. My strongest suit is developing intelligent systems that "see" and understand the world. I've built a retail analytics platform (CrowdIQ) that transforms standard CCTV into a source of business intelligence, tracking customer demographics and behavior. In the sports domain, I created PadelIQ, an analytics engine that uses computer vision to track player movement, posture, and court coverage from match footage, providing real-time coaching feedback. For public safety, I developed a traffic management system (OmniRoad AI) using advanced object detection for real-time accident and congestion monitoring. Beyond computer vision, I architect full-scale data science pipelines. A prime example is my telecom churn prediction project, where I built a machine learning model to identify at-risk customers and paired it with an interactive Power BI dashboard. This end-to-end approach—from data analysis to a clear visualization of insights—ensures the model's findings directly inform business strategy and retention actions. I also develop the tools and infrastructure that power AI applications. I've built secure, enterprise-grade systems like DevelmoGPT, a RAG-based LLM that allows for secure, semantic search over private company documents. From creating simple utilities like PDF-to-audio converters to designing complex role-based access systems, I ensure the foundation of any AI solution is reliable, secure, and maintainable. My process is collaborative and results-driven. I start by deeply understanding your business problem, not just the technical requirement. We'll then iterate through prototyping, development, and testing to ensure the final product not only meets specs but also delivers tangible ROI. I communicate clearly at every stage, providing demos and documentation so you're never in the dark. Let's connect. Share your project idea or challenge, and I'll provide a clear outline of how we can leverage AI, machine learning, or computer vision to build your intelligent solution. Click the invite button to start the conversation. /// The following is just for SEO. You can ignore it /// #computer vision #computer vision engineer #computer vision OpenCV #machine learning computer vision #deep learning computer vision #computer vision machine learning #machine learning python #nlp machine learning

Your business will reduce operational costs by 35% through 𝐀𝐈 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧, 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬, and intelligent process optimization that deliver measurable ROI within 90 days 🚀. With 8+ years of experience in 𝐚𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭, 𝐝𝐞𝐞𝐩 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐈 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭, I’ve built 40+ production-ready AI systems generating millions in value for fintech, manufacturing, healthcare, and e-commerce companies . 𝐇𝐞𝐫𝐞'𝐬 𝐡𝐨𝐰 𝐈 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 & 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: 🔹 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 & 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬: Supervised learning, unsupervised learning, anomaly detection, forecasting models, recommendation systems, and real-time decision intelligence delivering measurable business impact . 🔹 𝐍𝐚𝐭𝐮𝐫𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 (𝐍𝐋𝐏) & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈: AI chatbots, LLM integration, text summarization, sentiment analysis, document classification, and workflow automation reducing manual effort by 70% . 🔹𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 & 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Object detection, OCR, facial recognition, image segmentation, defect detection, and real-time video analytics achieving 95%+ accuracy . 🔹 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 & 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌𝐬): Custom GPT development, prompt engineering, fine-tuned models, Retrieval-Augmented Generation (RAG), AI copilots, and enterprise AI content automation boosting productivity . 🔹𝐌𝐋𝐎𝐩𝐬 & 𝐂𝐥𝐨𝐮𝐝 𝐀𝐈 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: Scalable AI architecture using TensorFlow, PyTorch, FastAPI, Docker, Kubernetes, AWS, and GCP with CI/CD and model monitoring ensuring reliability and performance . 𝐑𝐞𝐜𝐞𝐧𝐭 𝐀𝐈 𝐂𝐚𝐬𝐞 𝐒𝐭𝐮𝐝𝐢𝐞𝐬: ✅ FinTech Fraud Detection: Reduced false positives by 42% while processing $10M+ monthly transactions with real-time AI risk scoring . ✅ AI Customer Support Automation: Built an NLP-powered chatbot handling 70% of support queries, saving 100+ hours monthly with 95% satisfaction . ✅ Manufacturing Quality Control AI: Delivered a computer vision system achieving 95%+ accuracy and reducing defects by 60% . 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐞𝐬 𝐒𝐞𝐫𝐯𝐞𝐝: FinTech AI, Manufacturing AI, Healthcare AI, E-commerce AI, and Intelligent Customer Automation . 𝐈 𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞 𝐢𝐧 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐀𝐈/𝐌𝐋 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐢𝐧𝐭𝐨 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲, 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐭𝐡𝐚𝐭 𝐝𝐫𝐢𝐯𝐞 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐠𝐫𝐨𝐰𝐭𝐡 𝐚𝐧𝐝 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 . 𝐄𝐯𝐞𝐫𝐲 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐢𝐧𝐜𝐥𝐮𝐝𝐞𝐬 𝐫𝐨𝐛𝐮𝐬𝐭 𝐭𝐞𝐬𝐭𝐢𝐧𝐠, 𝐦𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐥𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲. Ready to leverage AI for competitive advantage? Let’s discuss your goals and expected ROI .

Freelance Machine Learning Engineer with 3+ years of experience building and deploying end-to-end Computer Vision models, AI pipelines, and generative image workflows from prototype to cloud production. CORE COMPUTER VISION SERVICES & EXPERTISE: • Object Detection & Tracking: Implementing and training YOLO (YOLOv8, YOLOv9, YOLOv10, YOLOv11), Faster R-CNN, and SSD architectures. Experienced in real-time object tracking using Byte Track (ByteTrack) and Bot SORT (BoT-SORT). • Image Segmentation & Classification: Custom semantic segmentation, instance segmentation, and image classification pipelines using PyTorch, TensorFlow, Keras, and OpenCV. • Generative AI & Image Generation: Advanced ComfyUI workflow automation, Stable Diffusion, Flux, Dreambooth fine-tuning, ControlNet, and IP Adapter integrations. • GANs & Image Processing: Image restoration, denoising, deskewing, despeckling, and super-resolution using Real-ESRGAN, ESRGAN, CycleGAN, and Neural Style Transfer (NST). • OCR & Document Intelligence: Optical Character Recognition (OCR) for structured documents, multi-format images, and noisy datasets. MLOPS, CLOUD INFRASTRUCTURE & DEPLOYMENT STACK: • Deployment & APIs: Building scalable REST APIs using FastAPI and Flask for serverless and dedicated model deployment. • Containerization & Orchestration: Docker containers and Kubernetes clusters for reproducible AI infrastructure. • Data & Experiment Management: MLOps pipelines utilizing DVC (Data Version Control) for data versioning and MLflow for machine learning experiment tracking. • Cloud Providers: Cloud architecture and deployment on AWS (Amazon Web Services), Runpod, Exoscale, Hugging Face Spaces, and custom Linux servers. TECHNICAL SKILLS & TOOLS MATRIX: Machine Learning • Computer Vision • Deep Learning • MLOps • Python • PyTorch • TensorFlow • Keras • OpenCV • Scikit-learn • Hugging Face • Diffusers • FastAPI • Flask • Docker • Kubernetes • MLflow • DVC • AWS • Runpod • Exoscale • YOLOv11 • ComfyUI • Stable Diffusion • Flux • Object Detection • Image Segmentation • OCR • Object Tracking