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AI Architect & Senior ML Engineer with 10+ years of academic + industry experience building production-grade intelligence systems, LLM pipelines, and multimodal AI. I design and deploy end-to-end ML architectures, including LLM orchestration, timeseries modeling, graph ML, OCR pipelines, and automated image-processing systems. Trusted by enterprises for high-reliability AI, data privacy, and scalable ML infrastructure.

I build LLM data pipelines, forecasting models, and production APIs for founders and small teams. From one-time analysis to product-grade systems. I co-founded a market-data startup, where I built an NLP pipeline that labels 1.5M+ news articles and shipped a production API. My research on LLM rerankers was accepted at SIGIR 2026, a leading conference for search and ranking systems. I also maintain open-source LLM tools, including a LangGraph agent CLI on PyPI and a local RAG tool with page-cited answers. I have a strong track record in: • LLM data pipelines: classification, labeling, sentiment scoring, and extraction • Production ML systems and APIs (FastAPI, Docker, AWS, Google Cloud, BigQuery) • Forecasting models for sales optimization and budget planning • Dashboards and decision tools • CRM data analysis (HubSpot, Zoho) • RAG systems and LLM agents (LangGraph), with testing and evaluation Founders and team leads typically work with me to: • Replace manual labeling, tagging, or reporting work with automated LLM pipelines • Add an AI feature to an existing product and make it reliable enough to ship • Build forecasting models on transaction, sales, or CRM data • Extract insights from complex data such as transactions, call records, and multi-source attributions • Turn an LLM prototype into a tested, deployed system I have 3+ years of freelance experience and 5+ years of hands-on data science and analytics. I've worked directly with founders and small teams, and delivered 40+ projects with a 100% success rate. I hold a Master's in Computer Science and a bachelor's degree in business, and I conduct applied research in machine learning for finance and NLP. What previous clients say: "Baris will always be the #1 choice in his category. Great guy. 10/10." "One of the best freelancers I've worked with. He understood quickly what I was trying to build." For larger projects, my usual structure is a short paid discovery to map the problem and the data, then a fixed-price build with clear milestones, so the budget is known before the work starts. Ongoing support is optional after that. If you have an LLM or data problem that needs to work reliably in production, feel free to send a message. I'll be happy to take a look.

Hi, I am an AI & Machine Learning Engineer specializing in Perception 3D, Computer Vision, Edge Computing, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Chatbot Development, Generative AI, Embedded Systems, and Firmware Development. Please get in touch if you need help with the following: • Machine Learning & Deep Learning model development • Computer Vision tasks like object detection, segmentation, and 3D reconstruction • Natural Language Processing (NLP) including text mining, sentiment analysis, and chatbots • Generative AI models for stock prediction, image inpainting, and virtual clothing • Time-Series Forecasting and Anomaly Detection • Firmware development for microcontrollers (ESP32, STM32, PIC) and IoT devices • Schematic and PCB design using Altium, KiCad, Eagle, and EasyEda • AWS IoT Core setup and cloud integration for IoT projects • Device driver development for various peripherals (I2C, SPI, etc.) • AI Deployment & MLOps with AWS, GCP, Docker, and Kubernetes • Data Analysis & Visualization for business intelligence Tools and technologies I use: • Python, C++, R, JavaScript • TensorFlow, Keras, PyTorch, Scikit-Learn, HuggingFace, LangChain • Zephyr RTOS, FreeRTOS, ESP-IDF • Flask, Django, Node.js • AWS IoT Core, GCP, Docker, Kubernetes • Altium, KiCad, Eagle, EasyEda • MongoDB, MySQL, PostgreSQL, Cloud SQL • Pandas, NumPy, Matplotlib, Seaborn, SciPy Do reach out if you need something other than this, I may be able to help out and guide.

I'm a machine learning engineer focused on building end-to-end ML pipelines, data science solutions, and LLM-powered applications. What I work on: -ML model development — classification, regression, ensemble methods (XGBoost, LightGBM, CatBoost) -End-to-end pipeline design with MLflow for experiment tracking and model registry -LLM integrations using LangChain, LlamaIndex, RAG, and OpenAI/HuggingFace APIs -AutoML workflows with H2O.ai, TPOT, Auto-sklearn My engineering background helps me think in systems — not just models. I've worked on a government-funded R&D project (TÜBİTAK), placed in the top 3% on Kaggle, and built automation systems in real factory environments. I care about clean code, honest communication, and solutions that actually work outside the notebook. Let's build something useful.

Top 3% Freelancer who built enterprise multi-tenant RAG systems with custom LLM deployments, reduced LLM workflow costs by 70%, and delivered a 2M product data quality pipeline for a Fortune 500 biotech company, reducing manual efforts by 85%. Architected and deployed production systems across finance, biotech, energy, telecommunications, and healthcare. 5+ years taking end-to-end ownership on all projects, from greenfield architecture to secure & scalable production deployment, leading engineers and maintaining systems long-term. I specialize in production-ready AI solutions with measurable ROI. From 90% accuracy voice classification to billion-scale data engineering. Core Expertise: • AI Agents / Agentic Workflows (LangGraph, Tool Calling, Function Calling, Agent Memory Patterns, Agent Patterns, Multi-Agent Orchestration, Building MCP, Plugins, Skills, Hooks, Deterministic Enforcement, ReAct Pattern, AI Assistants, Research, Planning, Writing) • LLM Systems (Claude API, OpenAI API Integration, vLLM, LoRA/QLoRA Fine-Tuning, PEFT, RLHF, DPO, LLaMA, Mistral, Prompt Engineering, Deterministic Workflows, LLM Evaluation, Cost Optimization, Deploying Chatbots, Deploying LLMs, Claude Code, Codex) • RAG (Hybrid Retrieval, Vector Databases, Evaluation Harness, Tiered Access, Custom Document Parsing, PDF/Clinical Data Extraction, Ragas, Multi-Tenancy) • NLP (Transformers, spaCy, Named Entity Recognition, Text Classification, Taxonomy Design, Rule-Based Extraction, Sentiment Analysis, Topic Modeling, Summarization, Information Extraction) • Generative AI (Structured Outputs, Pydantic Validation, Guardrails, Hallucination Prevention, AI Chatbot Development, AI Integration) • ETL & ML Pipelines • Time Series Applications at scale. - I personally prefer native APIs for building Agentic / LLM workflows. Domain Expertise: • Energy & Utilities (demand forecasting, carbon emissions, time series, pricing optimization) • Financial Services (compliance-ready RAG, churn prediction) • Life Sciences (biotech product classification, scientific NER, clinical data extraction, safety) • Telecommunications (voice classification, Whisper, ASR, diarization) Projects - Open source contributor (Langchain vLLM integration fix) - Enterprise RAG Engine with multi-tenancy, project-level isolation, custom vLLM deployments, agent live on the WhatsApp channel - customer support. - Finance-Specific RAG System with compliance features and RAG benchmarking - Enterprise Knowledge Base Chatbots Integrating (RAG daily sync on Notion, Slack, Website, Documents, evals, Live on Zendesk Customer Support Agent, Internal AI Agents on Slack(Deep Research, Q-A, Reporting), Blogpost creation with tone and fact checks.) - Production agentic workflows with state management, semantic processing, and monorepo CI/CD - SEO keyword clustering system processing 10k+ keywords under 10s using OpenAI embeddings + HDBSCAN - Enterprise Misspelling Detection Pipeline for 2M biotech products using FAISS similarity matching and 740k scientific corpus validation (Thermo Fisher) - Real-time Voice Classification System (90% accuracy, active learning pipeline) - Call Recommendation System with statistical engine for optimal calling times - Energy Market Forecast System for Budapest electricity prices - 500+ Class Text Classification with Fine-Tuned BERT - Extending a Lexicon using GloVe Word Embeddings - Databricks PySpark Data Pipeline for Aggregating Billion Scale Data - Time Series Analysis and Models on Energy Consumption Data from different locations in Belgium and Germany - API Integrations & Calculations on Electricity Business Objectives - Imbalanced Binary Classification on Anonymized Data (Oversampling + CatBoost & hGBM) - Data Processing Pipeline for 70m of Electricity Sensor Data for a Research Project Tech Stack: • Programming Languages: Python, SQL • Machine Learning & Deep Learning: TensorFlow, Keras, PyTorch, Scikit-Learn • NLP: LangChain, NLTK, Gensim, FAISS, Pinecone, pgvector • Time-Series: Prophet, TSMixer, ARIMA, SARIMAX, LSTM • MLOps & Data Engineering: Terraform, Linux, Apache Spark, Airflow, Docker, Flask, Streamlit, Gradio, MLflow, W&B, Optuna, CI/CD Pipelines, n8n workflows, Ragas • Cloud: Google (BigQuery, Cloud Functions, Cloud Run, Dataflow, Vertex AI, Firestore, Cloud Storage, Composer) • AWS (Lambda, SageMaker, S3, EC2, ECR, DynamoDB, Glue, CloudWatch) • Azure (Databricks-PySpark) • Database: PostgreSQL, Pinecone, Chroma • Data Manipulation & Statistics: Pandas, NumPy, OpenCV, Regex, SciPy, Statsmodels • Data Visualization: Matplotlib, Plotly • Web Scraping: BeautifulSoup, Requests • Building Custom NER Models & Linking, Question Answering, Text Similarity & Word Embeddings, Part-of-Speech Tagging & Dependency Parsing, Text Generation, Lexical Semantics & N-grams, Clustering • Logistic Regression, SVM, Decision Trees, Random Forest, Gradient Boosting Machines (XGBoost, LightGBM, hGBM), k-NN, CNN, RNN, K-Means, DBSCAN, HDBSCAN, OPTICS

🏆 AI & Machine Learning Specialist with PhD ✅ 12+ Years of Experience in Research & Development ✅ Bridging Academic Excellence with Real-World Applications 👋 Hello! I'm Murat, an experienced AI Specialist and Software Developer with a strong academic and practical background. For over a decade, I’ve delivered cutting-edge solutions in Machine Learning, Computer Vision, and Large Language Models (LLMs), combining research depth with industry impact. 🌟 Why Work With Me? • AI & ML Expertise: Extensive knowledge in deep learning, generative AI, and data-driven systems • LLMs & Agent AI: Skilled in building smart, multi-agent systems using modern LLM frameworks (e.g., GPT-4, Claude, Gemini) • Backend & Automation: Proficient in Python, Django, Flask, and API development • Web Scraping Pro: Automating data collection with Selenium, Beautiful Soup, and Scrapy • Blockchain-Ready: Experience with smart contracts (Solidity), NFTs, and Web3 systems 🤖 AI & Machine Learning Capabilities • Deep Learning (TensorFlow, PyTorch, Keras) • Natural Language Processing (NLP) • Computer Vision (image/video processing & analysis) • Generative AI & LLM integration (GPT-4, Claude, Gemini, etc.) • Agent-based AI architectures (LangChain, AutoGen, CrewAI) • Vector Search & Embeddings (Pinecone, FAISS, Chroma) 🔧 Software Development & Integration • Programming: Python, Java, MATLAB • OOP and Clean Code Principles • Web Frameworks: Django, Flask, FastAPI • API Development & Integration (RESTful APIs) • PostgreSQL & Data Management 🌐 Web Scraping & Automation • Advanced scraping tools: Selenium, Beautiful Soup, Scrapy • Data cleaning & analysis with pandas • Real-time data pipelines for analytics & dashboards 💬 Client Commitment I prioritize clear communication, quality delivery, and long-term value. Whether you're building an AI-powered platform, need a backend system, or want to extract and analyze complex data — I’m here to make it happen. 📩 Let’s turn your vision into results — feel free to reach out and discuss how we can work together!