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I am an associate professor of Mathematics with more than 10 years of work experience as a researcher and ML engineer. Being mathematician, I am good at basic Machine Learning algorithms: neural networks, compositions, decision trees, metric algorithms, linear algorithms, etc. I have experience in the following areas: Time Series: 1. Stock market pattern recognition; 2. Server attack prediction based on sensor data of server. NLP (Natural language Processing): 1. Document Classification; 2. Document Summarization. Computer Vision: 1. Check box detection and information extraction (digitization) from scanned documents; 2. Information extraction from scanned invoices (NLP Technics, Object detection); 3. Voice Classification (transformation voice mp3 data to graph, image (graph) classification); 4. An object detection model to help visually impaired customers to navigate in a shopping APP and make a purchase has developed. Object detection for 15 categories with their bounding box coordinates and implemented the logic of navigation have performed; 5. Segmentation model to detect lands suitable for sowing and calculating area has developed; 6. A model has been developed that counts the number of packages that are loaded onto a pallet in stock (object detection, tracking and counting technic is used).

I am a full-stack Python, C++ AI/ML/ Computer vision / 3d reconstruction developer ✅ Top Rated PLUS Upwork Freelancer ✅ 15000+ hours worked ✅ 120+ Jobs Completed ✅ $300k+ earned Computer Vision and Machine learning - Computer Vision | Machine learning OpenCV,PCL,ROS,Detectron,YOLO, VTK, Intel Realsense, Zed camera, Zivid camera, NLP, Transformers - Computer Vision, Image Processing, OpenCV, OpenGL, MKL, ITK, VTK - Deep Learning, caffe, Tensor flow, Pytorch - YOLO, DETECTRON -Desktop application development using C++/Qt, Python -3d reconstruction, NLP using Matlab,R, Python, OpenCV, OpenGL,CUDA,OpenCL, MKL, ITK, VTK,PCL,ROS,R, Transformers. -Machine and Deep Learning using SVM, KNN, Neural Networks(TensorFlow, Yolo, Detection, Pytorch). -GUI development, sockets. -Stereo Vision and 3d reconstruction. SLAM and SFM algorithms implementation and improvement. -Video/Audio streaming over network using LIBVLC, FFMPEG, GSTREAMER. -Natural language processing using BERT, BART. -Development of technically complex projects and scientific articles. -Generic programming, OOP. -Complex algorithms & data structures.

Hi there! I'm an AI Engineer specializing in Computer Vision, LLM Fine-Tuning, RAG Systems, and AI Agent Development. With 4+ years of hands-on experience in Machine Learning and AI engineering, I build intelligent, production-ready systems that help businesses automate workflows, analyze visual data, detect sensitive information, and make smarter decisions with AI. ⚙️ What I Do: • RAG & LLM Systems: Production RAG pipelines with semantic search, vector stores (ChromaDB), time-aware retrieval, and grounded LLM responses via OpenAI GPT-4o-mini and LangChain — deployed on GCP with Docker and GitLab CI/CD • LLM Fine-Tuning: End-to-end fine-tuning pipelines across Llama, Mistral, Gemma, Phi, DeepSeek, Qwen, and Granite for NLP classification tasks — including custom dataset construction, HuggingFace Trainer API, and benchmark evaluation • Computer Vision: Real-time object detection and tracking (YOLOv8/v11, ByteTrack, StrongSORT), multi-camera Re-ID with epipolar geometry, emotion recognition, and TensorRT/ONNX-optimized inference pipelines • AI Agents & Automation: LLM-powered agents, Celery-based data ingestion pipelines, chatbot development, and API-driven workflow automation with FastAPI • ML Model Development: CNNs, NLP, model training, fine-tuning, ONNX/TensorRT optimization, and scalable production deployment • AI Infrastructure: FastAPI, Docker, GCP, GitLab CI/CD, PostgreSQL, MongoDB, Redis, scalable AI app architecture 🧠 Tech Stack: Python · PyTorch · HuggingFace Transformers · LangChain · OpenCV · YOLOv8/v11 · ChromaDB · FastAPI · Celery · Docker · PostgreSQL · MongoDB · GCP · GitLab CI/CD · ONNX · TensorRT · Streamlit · Stable Diffusion · scikit-learn 🌟 Why Clients Work With Me: • End-to-end delivery — from data collection and model training to production deployment and maintenance • Hands-on experience across media, retail, urban planning, and data privacy domains • High focus on accuracy, low latency, and scalability • Clear communication, fast delivery, and strong problem-solving under real production constraints Let's bring your AI, Computer Vision, or LLM idea to life 🚀

I build credit scoring and loan default prediction models that help lenders approve more good borrowers, cut losses, and make underwriting decisions they can stand behind. I work in Python, and I focus on models that go into production not prototypes that get shelved. Before Upwork, I spent three years as an in-house Data Scientist at Ameriabank, one of Armenia's largest banks, building forecasting and risk models used in live operations. That experience shapes how I work: I care as much about how a model holds up over time and under review as I do about its accuracy on day one. I usually work with: — Fintech and alternative/SME lenders building or improving credit decisioning — Banks and credit unions that need scorecards built, rebuilt, or validated — Risk and analytics teams that need an extra pair of expert hands What I typically deliver: — Credit scoring and application/behavioral scorecards — Loan default prediction and PD models — PD / LGD / EAD modeling and IFRS 9 ECL work [ADD REAL PROJECT DETAIL] — Model validation, monitoring, and clear documentation — Risk segmentation and lending portfolio analytics — Fraud detection models for lending — Risk dashboards and SQL/Python pipelines that replace fragile Excel reporting Tools I rely on: Python (pandas, scikit-learn, statsmodels), XGBoost, LightGBM, logistic regression, and SQL, with FastAPI and Docker when something needs to be deployed. A few honest signals: Top Rated Plus, 100% Job Success, and $40K+ earned on Upwork. On a recent credit scoring project the client's feedback was simply "Highly recommended," and another noted my "amazing knowledge in ML and DS." [ADD REAL METRIC e.g. Gini/AUC, default-rate reduction, or approval-rate lift] How I work is straightforward: a short scoping call, then a clear plan with an honest estimate, then iterative delivery with documentation your team and any reviewer can actually follow. If something isn't the right fit for me, I'll tell you. Send a short message with your problem, your data, and your timeline. I usually reply within a few hours. The first 15-minute scoping call is free.

7+ years building production computer-vision, OCR, edge-AI, and AI backend systems where accuracy, latency, and reliability matter. Typical work includes defect detection, live video/object tracking, on-device model optimization, document/OCR pipelines, OpenAI/RAG integrations, and launch rescue for AI products that need evaluation, observability, and clean API architecture. My strongest fit is a project with real data, a broken or uncertain pipeline, and measurable acceptance targets: accuracy, false positives, latency, edge-device constraints, cost, security, or launch readiness. Core work: - Computer vision / OCR: detection, segmentation, tracking, image analysis, OCR extraction, validation, reviewer workflows - Edge AI: ONNX/TensorRT conversion, model optimization, quantization-aware deployment, mobile/on-device inference - AI backend: OpenAI API, RAG, VLMs, source traces, confidence checks, FastAPI, PostgreSQL - Production delivery: tests, logging, monitoring, cloud deployment, handoff docs I am a good fit when AI output must be accurate, fast enough for production, reviewable, logged, and reliable enough for real business use.

I'm a Data Scientist/Machine learning engineer, with more than 5 years experience, and Kaggle Expert (top 2%). My toolbox includes mathematical & statistical methods, machine learning algorithms, programming and domain knowledge. I'm focusing on Computer vision, OCR (optical text recognition), NLP (Natural Language Processing), Time Series Analysis, Data Analytics. I have successfully implemented the following projects:: - Face detection and recognition system for the Mall; - OCR system: document segmentation, alignment, quality improvement, super-resolution, information extraction; - Manage Parking spaces through surveillance cameras for the Mall; - Chat-bot for real estate company; - Profit prediction in retail chain stores; - Stocks market trading models. The effectiveness of solutions is confirmed by participation in Kaggle competitions (into the top 5% of the competition ranking). I will perform a full spectrum of works "on a turnkey basis" with the maximal quality. Starting from the problem statement, data preparation, to the construction of the finished model and analysis and visualization of the results, with the use best practice technique.