Hire the Best Artificial Intelligence Engineers

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)!

Most machine learning projects fail between the prototype and production. I've shipped 47+ that didn't. 🎯 YOLO Detection | 🧍 Pose Estimation | 🏋️ Sports AI | 🛒 Retail AI | 🛡️ CCTV Analytics | 🔄 Tracking | 🧠 ML Pipelines | 🤖 AI Agents | 💬 LLM Integration 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. Object detection · Machine learning · Pose estimation · Multi-camera tracking · Segmentation · Re-identification · Anomaly detection · OCR & ANPR · Optical flow · Depth estimation · LLM-powered reasoning · Agentic decision pipelines While most CV engineers stop at training the model, I go further: → Accelerated inference with TensorRT, ONNX, OpenVINO, and FP16/INT8 quantization (up to 5× faster) → LLM agents layered over CV pipelines for real-time decisions, alerts, and natural language outputs → Mobile deployment via CoreML (iOS) and TFLite (Android) with 10+ live apps shipped → Edge deployment on Jetson, OpenVINO, Apple Neural Engine, and CUDA/cuDNN → End-to-end pipeline: camera input → training → optimization → real-time actionable output Key Accomplishments: ⭐ Generated $5M+ in client revenue ⭐ Delivered 100+ end-to-end computer vision systems ⭐ Successfully launched my own 2 SaaS products ⭐ Real-time sports AI for 7+ sports, improving analytics for 15+ teams ⭐ Mobile AI on iOS (Core ML) & Android (TFLite), powering 10+ apps ⭐ Surveillance, safety, and industrial AI solutions ⭐ Medical imaging AI for 5+ hospitals: tumor detection, ultrasound, test strips ⭐ Model optimization: up to 5× faster inference using FP16/INT8, ONNX, TensorRT, OpenVINO ⭐ Multi-object tracking, re-identification, Model Training 1M+ labelled Dataset ⭐ Agentic CV systems that perceive, reason, and act without human input in the loop 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: - Sports & Fitness: athlete tracking, shot detection, scoring automation, drill analysis, pose estimation - Industrial & Workplace: tire defect inspection, PPE compliance, staff monitoring, meter reading, machine vision inspection, automated quality control - Surveillance & Security: ANPR, crowd monitoring, people counting, animal attack detection, exam cheating detection, perimeter security, intrusion detection - Healthcare & Medical: tumor detection, ultrasound processing, test strip analysis, X-ray/CT scan processing, lesion segmentation, medical image annotation - Traffic & Transport: aerial monitoring, traffic flow AI, license plate recognition, vehicle detection, accident detection, parking management - Retail & Business: customer analytics, receipt extraction, retail intelligence, object recognition, shelf monitoring, inventory management Tech Stack: Machine Learning, Deep Learning, YOLOv5, YOLOv8 - YOLO26, Detectron2, DeepSORT, StrongSORT, MMDetection, MediaPipe, OpenPose, PoseTrack, Action Recognition, Semantic Segmentation, Instance Segmentation, OCR, Anomaly Detection, Motion Detection, Object Counting, License Plate Recognition, PyTorch, TensorFlow, TensorFlow Lite, Keras, OpenCV, FastAPI, Flask, Core ML, TFLite, ONNX, TensorRT, OpenVINO, CUDA, Swift, Kotlin, Flutter, Python, C++, AWS, GCP, Azure, Edge Deployment, Mobile AI, Real-Time Inference, Surveillance AI, Aerial Drone Analytics, Video Stream Analytics, AI Automation, LLM Integration (GPT-4o, Claude, Gemini, Groq), AI Agent Frameworks (LangChain, LangGraph, CrewAI), RAG Pipelines, Streaming LLM Inference license plate recognition, aerial drone analytics, surveillance AI, mobile AI, embedded systems, deep learning pipelines, inference optimization, video stream analytics, AI automation, AI for industry 4.0, computer vision pipelines. 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.

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'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?

Computer Vision Expert | YOLO | Object Detection | Tracking | OpenCV | Deep Learning | Jetson | Real-Time Systems | Image/Video Labeling Specialist | Machine Learning | OCR With 5+ years of experience and 150+ successful projects, I help businesses build high-performance Computer Vision and Deep Learning systems for real-world applications. I specialize in Object Detection, Multi-Object Tracking, Image Segmentation, and Real-Time Video Analytics, delivering scalable AI solutions used in production environments. 🚀 What I Can Do For You ✔ Build Object Detection systems (YOLOv8, YOLO11, YOLO26) ✔ Develop Multi-Object Tracking (DeepSORT, ByteTrack, BOT-SORT) ✔ Create Real-Time Video Analytics pipelines ✔ Design Image Segmentation models (U-Net, DeepLabV3+) ✔ Develop Face Recognition & Liveness Detection systems ✔ Build OCR & Document AI solutions ✔ Optimize models using TensorRT, CUDA, GPU acceleration ✔ Deploy AI systems via APIs, Docker, Cloud (AWS), Jetson ✔ Provide high-quality Image & Video Annotation / Labeling 👁 Core Expertise • Computer Vision • Deep Learning • Machine Learning • Object Detection • Image Segmentation • Multi-Object Tracking • OpenCV • YOLO (YOLOv8, YOLOv11, YOLOv26) • Real-Time AI Systems • Video Processing • OCR & Document AI • Data Annotation & Labeling 🧠 Real-World Solutions I Build • Surveillance & Smart Monitoring Systems • Retail Analytics & Customer Tracking • Face Recognition & Identity Verification • Industrial Defect Detection • Medical Image Analysis • Traffic & Vehicle Detection Systems ⚡ End-to-End Development I handle complete AI pipelines: Data Collection → Annotation → Model Training → Optimization → Deployment You get a fully production-ready system, not just a model. 🛠 Tech Stack 🔹 Deep Learning PyTorch, TensorFlow, Keras, CNN architectures, YOLO variants 🔹 Computer Vision OpenCV, MediaPipe, OCR systems, real-time video processing, detection and tracking pipelines 🔹 Machine Learning Scikit-learn, XGBoost, classification, regression, clustering 🔹 Tracking & Optimization DeepSORT, ByteTrack, SORT, TensorRT, CUDA 🔹 Backend & Deployment FastAPI, Flask, Docker, AWS, Jetson 🔹 Languages Python, C++ 💡 Why Clients Hire Me ✔ 150+ successful projects ✔ 100% Job Success (Top Rated) ✔ Real-time, high-performance systems ✔ Scalable & production-ready solutions ✔ Strong optimization (FPS, latency, memory) ✔ Clear communication & fast delivery 📌 Quick Overview 150+ Projects • 100% Job Success • Top Rated 🎯 Computer Vision — YOLOv8/11/26, Faster R-CNN, U-Net 📍 Tracking — DeepSORT, ByteTrack, BOT-SORT ⚡ Real-Time AI — OpenCV, PyTorch, TensorFlow 🧠 Deep Learning — CNNs, Vision Transformers 📄 OCR & Document AI — Tesseract, Google Document AI 🚀 Deployment — TensorRT, CUDA, Docker, AWS, Jetson 📩 Call to Action Looking to build a Computer Vision system, Object Detection model, or Real-Time AI solution? 👉 Send me a message — I’ll help you design the best approach and deliver a scalable, production-ready solution.

🤖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