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😱 𝗟𝗲𝘁’𝘀 𝗷𝘂𝗺𝗽 𝗼𝗻 𝗮 𝑭𝑹𝑬𝑬 𝑪𝑨𝑳𝑳 𝗮𝗻𝗱 𝗱𝗶𝘀𝗰𝘂𝘀𝘀! 😱😱😱😱😱😱😱😱 so you can see my approach before deciding. I build production-ready AI and trading automation systems for clients who need more than a simple script. I am an AI/ML engineer with a Master’s degree in Artificial Intelligence and hands-on experience building trading automation, prediction-market tools, real-time data pipelines, dashboards, and AI-powered analysis systems. I help traders, founders, and technical teams turn trading ideas into working software: from data collection and backtesting to live monitoring, bot execution, alerts, dashboards, and AI-based decision support. My work combines AI/ML engineering, real-time market-data infrastructure, trading bots, dashboards, and deployment. I can help you move from an idea or manual workflow to a working system that collects data, analyzes signals, executes logic, sends alerts, stores results, and runs reliably on a VPS or cloud server. Recent project areas include Kalshi and Polymarket prediction-market systems, Webull bot interfaces, real-time WebSocket feeds, Telegram/Discord trading controls, ClickHouse/Grafana dashboards, Docker deployments, and AI-powered market-analysis pipelines. My recent work includes building and improving systems for Kalshi, Polymarket, Webull, and crypto/prediction-market workflows, including real-time WebSocket data processing, order book monitoring, Telegram/Discord bot interfaces, market-data dashboards, database pipelines, and Docker-based deployment on VPS/cloud infrastructure. What I can help you build Trading bots and automation tools Kalshi, Polymarket, Webull, crypto, and broker/API integrations Real-time market-data pipelines WebSocket order book, ticker, trade, and price-feed processing Backtesting and strategy research tools Telegram/Discord trading bots and alert systems AI-powered market analysis and signal-generation workflows Dashboards for monitoring trades, PnL, token usage, prices, and system health Dockerized deployment, logging, debugging, and VPS/cloud setup Data storage using PostgreSQL, ClickHouse, and related tools AI/ML experience I also have strong experience in deep learning and applied AI, including: PyTorch, TensorFlow, Keras, scikit-learn LLM and AI-analysis pipelines generative models: Audio/music/speech AI systems Computer vision and object detection Data analysis, feature engineering, and model evaluation Python automation and production ML workflows Trading-system experience I have worked on systems involving: Kalshi prediction-market bots Polymarket data monitoring and dashboards Webull bot interfaces Real-time price feeds I focus on practical, production-oriented development: clean Python code, clear communication, reliable deployment, and systems that can be monitored, debugged, and improved over time. I can work on trading infrastructure involving real-time market data, WebSocket feeds, order books, execution workflows, monitoring dashboards, and low-latency automation. For more advanced trading architecture such as HFT-style systems, OMS/EMS design, and institutional execution workflows. If you have a trading idea, AI workflow, automation task, or market-data problem, I can help you turn it into a working system. # Technical stack Python, PyTorch, TensorFlow, scikit-learn, Pandas, NumPy, PostgreSQL, ClickHouse, Grafana, Docker, Linux VPS, WebSockets, REST APIs, Telegram bots, Discord bots, OpenAI API, trading APIs, and AI/ML pipelines. I work best with clients who want clear communication, fast iteration, and practical engineering. I can help with research prototypes, MVPs, production grade bots, dashboards, infrastructure, or debugging existing systems. # Keywords : Algorithmic Trading, Algo Trading, Quant Trading, Quant Developer, Trading Bot, Trading Automation, Trading Strategy, Strategy Development, Backtesting, Live Trading, Paper Trading, HFT, Low Latency, Market Making, Order Book, Level2 Data, Level3 Data, Tick Data, Market Data, Execution Engine, OMS, EMS, DMA, Smart Order Routing, Risk Management, Position Sizing, Portfolio Management, Portfolio Optimization, Signal Generation, Alpha Research, Statistical Arbitrage, Pairs Trading, Mean Reversion, Momentum Trading, Trend Following, Scalping, Arbitrage, Options Trading, Futures Trading, Forex Trading, Crypto Trading, Equities Trading, Prediction Markets, Kalshi, Polymarket, Webull, Interactive Brokers, IBKR, Alpaca, Binance, Coinbase, MetaTrader, MT4, MT5, MQL4, MQL5, TradingView, Pine Script, NinjaTrader, QuantConnect, Lean, NautilusTrader, cTrader, FIX API, Broker API, Exchange API, REST API, WebSocket, Trade Execution, Order Routing, Order Management, Fill Handling, Slippage, Latency Optimization, Market Microstructure, Volatility, Greeks, Delta Hedging, Options Spreads, Credit Spreads, Debit Spreads, Short Premium, Risk Controls, Stop Loss, Take Profit, Trailing Stop, PnL Tracking, Trade Alerts, Telegram Bot, Discord Bot,

Hello, I am investing all my time and resources in Upwork ☝ ⬣ My experience covers: data analysis, AI/ML model training, fine tuning and deploying into production AWS/GCP/Azure infrastructure or on edge devices. ⬣ Skills : GenAI - RAG, LLM finetune, AI Agent development, VLM, Vector Databases Machine Learning : classification, regression, similarity search Computer vision : classification, object detection, object tracking, pose estimation, video analytics system creation ⬣Programming languages : Python, MATLAB,C# ⬣ ML/DL LIBRARIES : TensorFlow, Scikit-Learn, Keras, Pandas, Numpy, OpenCV,Pytorch, HuggingFace,Unsloth, Ultralytics ⬣ Inference enginers: llama.cpp, OLlama, LiteRT-LM, TensorRT ⬣ Certificates : ✅ AWS Certified Solutions Architect Professional ✅ AWS Certified Solutions Architect Associate ✅ AWS Certified Cloud Practitioner ✅DeepLearning.AI Machine Learning Engineer for production ✅Hugging Face AI Agents Course I AM READY TO IMPLEMENT YOUR PROJECT AND CONVERT YOUR IDEAS INTO A REALITY!

PhD-trained Machine Learning Engineer and Research Scientist with 15+ years in software development and 7+ years applying ML to real-world problems. I combine academic rigor with engineering expertise to deliver solutions that work in both research and production. I have collaborated with startups, R&D teams in large corporations, and academic labs, applying ML across healthcare, genomics, predictive analytics, finance, and industrial applications. My experience also includes applied research in exploration geophysics and marine seismic, giving me a unique cross-disciplinary perspective. Notable projects include: Financial NLP: Built an LSTM-based system to detect special banking offers in documents — still outperforming competing solutions in speed and accuracy years after deployment. Biomedical ML: Developed a production-grade model for non-invasive heart stroke prediction using seismocardiography (SCG) data. Predictive Maintenance: Contributed to startup projects building anomaly detection and forecasting systems for industrial equipment. My technical toolkit includes: Languages & Libraries: Python, R, Matlab, C/C++, scikit-learn, TensorFlow, PyTorch, Keras, Transformers Cloud & Infrastructure: AWS (SageMaker, EC2, S3), Docker, Databricks, CI/CD pipelines, testing frameworks Expertise: LLM deployment & fine-tuning, production-ready ML systems, applied research Whether supporting scientific research or delivering scalable ML systems, I bring a proven ability to move projects from prototype to production.

I am a passionate mobile developer working both in native and cross-platform (Flutter). I have 5+ years of enterprise experience and a double Master's degree in Business Information Systems. My credo: • Clean code; • Beautiful apps; • Transparent working process My core skills are: − Client-server applications; − Machine learning; − Video streaming; − Augmented reality (AR).

I'm a data scientist and AI engineer with a few years of production experience with predictive modeling, multi-agent systems, RAG pipelines, end-to-end deployment. Some things I've shipped: an energy expert chatbot for politicians and policy staffers, a multi-agent customer support system across email, chat and SMS, and a regressive income prediction model approved by the National Bank of Georgia for a 10M GEL pilot. I work in Python primarily, stack includes: LangChain, LangGraph, FastAPI, scikit-learn, XGBoost, Supabase, Pinecone. On the frontend with React/TypeScript. I've also shipped a production iOS app in Swift. I care about building things properly, not just getting them to work once. If you've got a serious project, let's talk.

I architect intelligent autonomous AI agents and Python-based machine learning systems that slashed operational costs by 40% for a Fortune 500 retailer. My expertise in data analytics, data analysis, and data visualization allows me to transform raw SQL and Microsoft Excel datasets into high-ROI strategic assets. I specialize in Data Engineering and AI Integration to automate complex decision-making, optimize workflows, and unlock new revenue opportunities through artificial intelligence. My work consistently bridges the gap between data science and measurable business performance: • Reduced customer support costs by 60% through AI chatbot development powered by natural language processing. • Deployed real-time fraud detection agents preventing $2.3M in potential losses. • Built predictive machine learning models that lifted SaaS revenue by 35% through integrated analytics. • Designed Power BI and Excel dashboards for marketing automation, improving conversions by 33%. • Created ETL pipelines handling 1M+ records daily with 99.9% uptime for data engineering reliability. • Engineered PostgreSQL-based API integration for real-time business intelligence. • Developed a Python data visualization framework in Looker Studio and Excel for executive BI insights. • Built AI-driven quality control systems that reduced defects by 22%, saving $1.2M annually. • Introduced QA automation and data annotation pipelines to improve model accuracy by 18%. • Automated workflows using n8n and Node.js to streamline scripting and automation processes. • Optimized BigQuery data architecture to accelerate query speeds by 50%, enabling faster real-time decision-making. • Spearheaded a custom AI App Development project that integrated Google Analytics data, resulting in a 25% increase in user retention. My technical ecosystem spans Python, SQL, Power BI, BigQuery, PostgreSQL, AWS, and Looker Studio—bridging data analysis, AI integration, and data visualization. I leverage Deep Learning and AI agent development to translate analytics into strategic action, ensuring every system delivers measurable ROI. Let’s connect to design an AI-driven automation strategy that scales with your business.