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.

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.

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.

🌐🚀 MVP / SAAS Specialist Expertise in | AI Developer | RAG | LLM | AI Integration | Python | OpenAI API Integration | Artificial intelligence | Machine Learning | Langchain | Django React JavaScript | FastAPI | AI agent | AI App Development | AI bot | AI chatbot | AI Agent | Restful API | PostgresSQL | Botpress | PostHog | MCP Server | Multi-Agents/Multiple Agents | Voice AI 🔑 𝐈 𝐛𝐮𝐢𝐥𝐝 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲 𝐜𝐮𝐬𝐭𝐨𝐦 𝐰𝐞𝐛 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬, AI-Powered MVP, AI Healthcare Tools, AI Writing Tool, GPT Clone, Full Stack Application, Multi-Tenant 𝐚𝐧𝐝 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐬𝐨𝐥𝐯𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬, 𝐜𝐫𝐞𝐚𝐭𝐞 𝐧𝐞𝐰 𝐯𝐚𝐥𝐮𝐞, 𝐚𝐧𝐝 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐮𝐬𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬. 🎁 A 100% refund, if I'm unable to meet our agreed commitments. No questions asked! 𝐊𝐞𝐲 𝐅𝐚𝐜𝐭𝐬: 🧑‍💻 8+ years of experience as a Full Stack Developer and Artificial Intelligence Specialist 🚀 50+ market-winning projects launched ⌛ Around 600 hours on Upwork 🎯 Top-Rated on Upwork 🌉𝐈'𝐯𝐞 𝐬𝐨𝐥𝐯𝐞𝐝 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐟𝐨𝐫 𝐭𝐨𝐩 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐚𝐧𝐝 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐚𝐫𝐨𝐮𝐧𝐝 𝐭𝐡𝐞 𝐠𝐥𝐨𝐛𝐞 ☑️ Under Armour ☑️ Snowflake ☑️ Estateza ☑️ SearchLook ☑️ Sparrowcharts 💡 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐈 𝐛𝐫𝐢𝐧𝐠 𝐭𝐨 𝐲𝐨𝐮𝐫 𝐭𝐚𝐛𝐥𝐞? ☑️ Full Stack Development for robust and scalable web applications, including both front-end and back-end technologies ☑️ Custom Web and Application Development utilizing frameworks like Python, React, Django, React.js / Angular / Next.js / Nest / Nust / Golang and Node.js ☑️ Expertise in LLMs and ChatGPT integration to enhance application functionalities ☑️ Proficiency in RESTful APIs, GraphQL, and database management ☑️ Experience with cloud services like AWS, Azure, and Google Cloud for deployment and scaling ☑️ Strong problem-solving skills and ability to optimize user experiences and application performance 🌟𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐡𝐚𝐯𝐞 𝐭𝐨 𝐬𝐚𝐲 𝐚𝐛𝐨𝐮𝐭 𝐦𝐞: 🌟 Ali Hamza is in the top tier of software developers and data engineers. He is far more than an implementer; he is a strong architect. During this project set, Usama worked on data from major US corporations 🌟 One of the best developers I have ever worked with. He is always on time and does exactly what he says he will do. I could not recommend him enough. 🎯 𝐈 𝐩𝐨𝐬𝐬𝐞𝐬 𝐞𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐭𝐡𝐞 𝐟𝐨𝐥𝐥𝐨𝐰𝐢𝐧𝐠 𝐝𝐨𝐦𝐚𝐢𝐧𝐬 ☑️ Full Stack Development: ☑️ Backend: ☑️ Python ☑️ Django ☑️ Flask ☑️ NodeJs, Express.js ☑️ Rest API, SOAP ☑️ Websocket ☑️ Third party integration ☑️ Frontend: ☑️ Html5, Css3, Bootstrap ☑️ Javascript ☑️ ReactJs, Angular ☑️ VueJs ☑️ NextJs, NuxtJs ☑️ Ajax, JSON, XML, XHTML, SVG, Canvas ☑️ API integration, OpenAI API ☑️ DevOps: ☑️ CI/CD Pipelines ☑️ IaC ☑️ Docker ☑️ Kubernetes / Terraform ☑️ Elasticsearch ☑️ Cloud Computing (Azure, AWS, Google Cloud) ☑️ Version Control (Git, GitHub) ☑️ Containerization + Orchestration (Docker, Kubernetes) ☑️ Spring Boot / Java, Microservices Architecture ☑️ Real-time / Streaming / Event-driven architectures ☑️ Session Recordings / Session Replays ☑️ GraphQL / gRPC ☑️ Kafka / Redpanda (real-time streaming) ☑️ Generative Artificial Intelligence (GenAI) ☑️ Large Language Models (LLMs) ☑️ Natural Language Processing (NLP) ☑️ ChatBots and Virtual Assistants ☑️ Text to Image Modelling ☑️ Vector Databases ☑️ Retrieval-Augmented Generation (RAG) ☑️ ChatGPT ☑️ OpenAI ☑️ AI/ML (Artificial Intelligence + Machine Learning) ☑️ Multimodal AI / NLP ☑️ Agentic AI / Autonomous Agents ☑️ “Vibe Coding” / AI-first / prompt-driven dev workflows ☑️ Explainable AI / Ethical, Sustainable AI ☑️ Edge AI / On-device / Federated Learning ☑️ Web Scraping ☑️ Data Extraction ☑️ Data Scraping ☑️ Scrapy ☑️ Selenium ☑️ Beautiful Soup ☑️ Requests ☑️ Deployment and scheduling the scraping scripts on server ☑️ PostHog / Mixpanel / Amplitude / Segment (Twilio Segment) ☑️ OpenTelemetry (Datadog / Grafana / Sentry ☑️ LaunchDarkly / GrowthBook / VWO / Optimizely / Klaviyo ☑️ Airbyte / Fivetran / DBT ☑️ Auth0 / Clerk / SuperTokens / Google Auth ☑️ Stripe / Paddle ☑️ Plaid AI + Analytics Integrations ☑️ LangSmith / LangFuse – Observability and evaluation layer for LLM apps. ☑️ Weaviate / Pinecone / Qdrant – Vector DBs for AI features with analytics hooks. ☑️ Whylabs / Arize AI – ML observability & monitoring (similar to PostHog but for models). I am a Fullstack AI Developer - Python Django, React, Flask, API Integration I can help you to build: ⚡ Fast MVP Development (AI-Powered) ✅ ⚡ AI Powered SAAS Applications ✅ ⚡ AI Agent RAG Systems | AI Chatbots ✅ ⚡ Open AI API Integrations / LLM ✅ ⚡ Full stack Development (AI/ML, Django, React) ✅ ⚡ AI Workflows Automation ⚡ Voice AI tools Thank you for visiting my profile. Looking forward to working with you! I will 💲REFUND 💲, if your expectation wont meet. For reference, you can see my work and testimonials below. Lets Chat!

Most computer vision projects fail not in training — but in deployment. Models that hit 95% accuracy in the lab break down when lighting shifts, hardware stutters, or the camera feed isn't clean. I build systems engineered to survive those conditions — and I've done it across industries, hardware platforms, and deployment environments. I'm a Computer Vision Engineer specializing in end-to-end AI pipelines — from raw camera input to real-time inference, deployed on edge hardware, cloud APIs, or both. ━━ Core services ━━ → Object detection & multi-object tracking — YOLOv8, YOLOv5, ByteTrack, BOTSort, MMDetection → Segmentation, pose estimation & keypoints — MediaPipe, custom model architectures → Edge AI deployment — NVIDIA Jetson Orin/Nano, Raspberry Pi, Hailo — TensorRT, ONNX, INT8/FP16 → Cloud & API deployment — FastAPI, Docker, AWS GPU instances, REST & WebSocket inference APIs → Video analytics & smart camera systems — safety monitoring, defect detection, zone tracking, people counting ━━ Systems I've shipped ━━ ✓ Real-time fall detection on NVIDIA Jetson — production-deployed, sub-100ms latency ✓ Zone-based people tracking & monitoring for safety-critical environments ✓ Industrial defect detection pipeline — TensorRT-optimized, running on constrained edge hardware ✓ End-to-end smart camera system: camera → inference → dashboard & real-time alerts ✓ OpenCV video analytics pipelines with custom pre/post-processing and business logic ━━ What makes my work different ━━ Most CV engineers deliver a model file. I deliver a working system — optimized, integrated, and running reliably in your environment. I lead a small team and personally own system architecture, optimization strategy, and core AI engineering on every project. You get senior-level technical execution, not delegation to juniors. Edge or cloud. Jetson or GPU server. Prototype or production scale. I've built across all of it. ━━ How a typical project runs ━━ 1. Discovery — review your hardware targets, data sources, and latency requirements before any code is written 2. Architecture — design the full pipeline: model selection, optimization path, deployment stack, integration points 3. Build & optimize — iterative development with benchmarked FPS and accuracy metrics at each stage 4. Deployment — containerized, documented, and running on your target environment 5. Handover — clean codebase, inline documentation, and a session so your team can maintain it independently ━━ Full tech stack ━━ Models: YOLOv8, YOLOv5, YOLOv7, MMDetection, Detectron2, PyTorch, TensorFlow, ONNX Runtime Tracking: ByteTrack, BOTSort, DeepSORT, StrongSORT, custom zone logic & counting algorithms Optimization: TensorRT INT8/FP16, ONNX quantization, model pruning, batch inference tuning Edge hardware: NVIDIA Jetson Orin/Nano, Raspberry Pi 4/5, Hailo-8, Coral TPU Cloud & infra: FastAPI, Flask, Docker, AWS EC2/Lambda, GCP, RTSP/RTMP stream processing Vision utilities: OpenCV, FFmpeg, GStreamer, PIL/Pillow, custom pipeline components ━━ Project types I take on ━━ → Greenfield CV systems — full pipeline from scratch to production deployment → Model optimization — take an existing model and make it production-fast on your hardware → Edge porting — migrate a cloud-based CV system to Jetson, Raspberry Pi, or Hailo → Pipeline debugging — diagnose and fix latency, accuracy, or stability issues in live systems → Inference API — wrap your CV model as a scalable, low-latency REST or WebSocket API → PoC → production — take a working demo and harden it for real-world deployment at scale → Team augmentation — embedded senior CV engineer for sprints or longer-term engagements ━━ Industries served ━━ Manufacturing & quality control — defect detection, visual inspection, production line monitoring Safety & security — real-time threat detection, perimeter monitoring, crowd analytics Retail & logistics — shelf analytics, people counting, queue management, warehouse tracking Healthcare — patient monitoring support systems, lab automation, medical imaging pipelines Agriculture — crop health detection, drone-based aerial inspection, field monitoring systems ━━ Common questions ━━ Work with our existing dataset? Yes — I assess quality, recommend augmentation strategies, and fine-tune models on your labeled data. Edge or cloud deployment? Both — Jetson, Raspberry Pi, and Hailo at the edge; AWS GPU instances and containerized APIs in the cloud. Can you take our prototype to production? That's one of my most common engagements — hardening, optimizing, and deploying existing concepts for real-world reliability. Documentation and handover included? Always. Clean code, inline comments, deployment instructions, and a dedicated handover session on every project. If you need computer vision that performs beyond lab conditions — on real hardware, with real data, in real-world environments — let's talk.

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)!