Hire the Best Machine Learning Engineers
in Kazakhstan

As a seasoned professional with 20 years of experience in back-end development and 7 years in machine learning, I have a proven track record of building high-quality, scalable web applications, APIs, and AI solutions. I am proficient in both front-end and back-end development, leveraging a wide array of technologies to deliver seamless user experiences, robust server-side solutions, and advanced machine learning models. WEB DEVELOPMENT Back-End: Building robust server-side logic with Django, FastAPI, and Flask. Full Stack: Seamlessly integrating front-end and back-end technologies for comprehensive solutions. API DEVELOPMENT RESTful APIs: Designing and implementing APIs with Django REST Framework. Microservices: Developing scalable microservices using Flask and FastAPI. Data Management: Utilizing SQLAlchemy and Alembic for efficient database interactions. Data Validation: Ensuring data integrity with Pydantic. DATABASE DEVELOPMENT Relational Databases: Designing and managing schemas in PostgreSQL. Analytical Databases: Implementing high-performance data storage solutions with Clickhouse. GUI DEVELOPMENT Desktop Applications: Creating user-friendly desktop applications using Qt/PyQt. AUTOMATION AND BOTS Telegram Bots: Developing bots for various purposes on the Telegram platform. Console Utilities: Automating text manipulation, email handling, image processing, and other routine tasks. MACHINE LEARNING & DEEP LEARNING Model Development: Design, train, and optimize machine learning and deep learning models. Frameworks: Proficient with TensorFlow, PyTorch, Keras, Scikit-learn. Hyperparameter Tuning: Expert in techniques to improve model performance. COMPUTER VISION Image Processing: Object detection, image classification, segmentation. Libraries: OpenCV, YOLO, SSD, Mask R-CNN. NATURAL LANGUAGE PROCESSING (NLP) Text Analysis: Sentiment analysis, text summarization, named entity recognition. Tools: NLTK, SpaCy, BERT, GPT, Transformers. RECOMMENDER SYSTEMS Personalization: Collaborative filtering, content-based filtering, hybrid methods. Implementation: Building recommendation engines to enhance user experience. DATA ENGINEERING Workflow Orchestration: Apache Airflow, dbt. Data Management: Clickhouse, Metabase, Apache Nifi. ETL Processes: Extract, transform, load workflows for data warehousing. Data Preparation and Exploratory Data Analysis (EDA) Data Cleaning: Handling missing values, outlier detection. Visualization: Creating insightful visualizations using Matplotlib, Seaborn, Plotly. Statistical Analysis: Descriptive statistics, hypothesis testing. MODEL DEPLOYMENT Deployment Platforms: AWS SageMaker, Google AI Platform, Azure ML. Frameworks: Flask, FastAPI, Starlite. Containerization: Docker, Kubernetes for scalable deployment solutions. ADDITIONAL SKILLS Programming Languages: Python, TypeScript, SQL, C++, Rust, JavaScript. Web Frameworks: Django, Flask, FastAPI, React. ORM: SQLAlchemy. Migrations: Alembic. Data Validation: Pydantic. Version Control: Git, GitHub, GitLab. DevOps: Docker for containerization and orchestration. PROFESSIONAL ATTRIBUTES Strong problem-solving skills with an analytical mindset and a passion for clean, efficient code. Excellent communication, teamwork, and collaboration abilities. Commitment to continuous learning and staying updated with the latest advancements in both web development and AI/ML technologies.

𝗥𝗲𝗮𝗰𝗵 𝗼𝘂𝘁 𝗮𝗻𝗱 𝗰𝗹𝗮𝗶𝗺 𝘆𝗼𝘂𝗿 𝗳𝗿𝗲𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝘁𝗶𝗼𝗻 + 𝟑𝟎‑𝗺𝗶𝗻 𝗔𝗜 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝘀𝗲𝘀𝘀𝗶𝗼𝗻 - 𝘆𝗼𝘂𝗿 𝗳𝗶𝗿𝘀𝘁 𝘀𝘁𝗲𝗽 𝘁𝗼𝘄𝗮𝗿𝗱 𝗿𝗲𝗮𝗹, 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗔𝗜 🎁 I help companies turn AI from a buzzword into a scalable, production‑ready capability. No demos. No prototypes that never ship. I build real AI inside your real stack - fast, reliably, and with measurable business impact. If you need an engineer who understands both deep ML and serious backend architecture, you’re in the right place. 🔥 What I Deliver: 1. AI Solutions & RAG Systems End‑to‑end design and implementation of Retrieval‑Augmented Generation systems tailored to your data, workflows, and security requirements. Tech: Node.js, TypeScript, Python, LangChain, Qdrant, REST, Ollama / HF 2. LLM & Vision Model Deployment Optimized, scalable deployment of LLMs and Vision models - on‑prem, cloud, or hybrid. Tech: PyTorch, Transformers, vLLM, Triton, KServe, Kubernetes 3. Vector Search & Knowledge Systems High‑performance semantic search, embeddings pipelines, and multimodal retrieval. Tech: Elasticsearch, SBERT, Mistral, Llama2, PostgreSQL, Redis 4. MLOps & ML Pipelines Robust, automated ML infrastructure for training, evaluation, monitoring, and CI/CD. Tech: Airflow, ClearML, MLflow, DVC, Kubeflow, Seldon, GitLab / Argo / GitHub CI 5. Backend Engineering & Microservices Scalable backend systems that integrate seamlessly with your AI components. Tech: Node.js, TypeScript, Nest.js, PostgreSQL, MongoDB, Redis, RabbitMQ Let’s map out your architecture, identify quick wins, and design a roadmap that gets you to production 🚀

You don't need another AI demo that breaks in production. You need someone who tells you upfront: this will work, this won't, here's why. Last quarter I fixed a hallucinating RAG for 1,000+ lawyers (AiExpert) and deployed a FinTech agent processing Visa/Mastercard docs at 95% accuracy (Shift4). ⚡ RECENT ENGINEERING WINS: - 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐑𝐀𝐆 - 𝐄𝐦𝐬𝐭𝐞𝐞𝐥 (𝐀𝐛𝐮 𝐃𝐡𝐚𝐛𝐢): Built a technical documentation assistant for factory operators. Improved retrieval accuracy from 0.82 to 0.93 (Faithfulness/Recall) using Hybrid Search and custom chunking strategies. - 𝐅𝐢𝐧𝐓𝐞𝐜𝐡 𝐀𝐠𝐞𝐧𝐭 - 𝐒𝐡𝐢𝐟𝐭𝟒 (𝐕𝐢𝐬𝐚/𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐚𝐫𝐝): Developed a parsing agent for unstructured PDF guides + ML model to predict transaction fees. Replaced manual calculations with 95%+ accuracy. - 𝐋𝐞𝐠𝐚𝐥 𝐓𝐞𝐜𝐡 𝐒𝐚𝐚𝐒 - 𝐀𝐢𝐄𝐱𝐩𝐞𝐫𝐭: Engineered a secure document analysis system for 1,000+ lawyers. Reduced review time by 60% with a scalable microservices architecture. - 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐫 𝐒𝐲𝐬𝐭𝐞𝐦 - 𝐂&𝐀: Built a product recommendation engine for millions of monthly active users. Achieved 8% NDCG uplift and 3% conversion increase. - 𝐂𝐨𝐧𝐜𝐢𝐞𝐫𝐠𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭 - 𝐊𝐢𝐧𝐠𝐬𝐰𝐞𝐥𝐥: Built Telegram & WhatsApp bots for real estate concierge service. Automated lead qualification and property viewing bookings. ⚙️ MY ENGINEERING APPROACH: - 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐑𝐀𝐆: No naive "text-splitting". I build GraphRAG & Hybrid Search (Sparse/Dense) systems with Ragas evaluation pipelines to eliminate hallucinations. - 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬: Orchestrating autonomous agents (LangGraph) that can plan, execute tools, and validate outputs. - 𝐓𝐫𝐮𝐞 𝐏𝐫𝐢𝐯𝐚𝐭𝐞 𝐀𝐈: Deploying Open Source LLMs (Llama 3.1/3.2, Qwen 2.5, DeepSeek) on your own infrastructure (On-prem/AWS GPU) using vLLM. Zero data leakage. 🛠 TECHNICAL TOOLKIT: 𝐋𝐋𝐌 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: LangChain, LangGraph, LlamaIndex, DSPy. 𝐎𝐩𝐞𝐧 𝐒𝐨𝐮𝐫𝐜𝐞 𝐌𝐨𝐝𝐞𝐥𝐬: Llama 3.1/3.2, Mistral Large, Qwen 2.5, DeepSeek-Coder. 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞 & 𝐒𝐞𝐫𝐯𝐢𝐧𝐠: vLLM, Ollama, Hugging Face TGI, Docker. 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: Qdrant (Self-hosted), Pinecone, Weaviate. 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 & 𝐂𝐨𝐫𝐞: Python, FastAPI (Async), Pydantic, PostgreSQL. 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧: YOLO11/v8, OpenCV, PyTorch. Previously: DataArt, EPAM, Grid Dynamics. MSc in AI (ITMO). Ready to build architecture, not just a chatbot? Invite me to your job.

I have over 4 years of experience in Data Science and around 5 years in programming, combining a strong mathematical foundation with hands-on expertise in machine learning, deep learning, and artificial intelligence. My academic background in Computer Science and practical experience across Big Data, analytics, and AI-driven systems have allowed me to deliver end-to-end solutions for complex business challenges. My professional journey began with competitive programming during school, followed by developing large-scale AI and data analytics projects for leading companies. Today, I specialize in building intelligent chatbots and analytical systems that merge technical excellence with a business-oriented mindset. I design adaptive dialogue flows, perform exploratory data analysis, create interactive dashboards and develop machine-learning models that optimize real business processes. Areas of Expertise 1. Computer Vision: Image classification, segmentation, object detection, facial recognition 2. Natural Language Processing (NLP): Text classification and generation, machine translation, sentiment analysis, LLM fine-tuning (Mistral, Hugging Face) 3. Data Analytics: Exploratory Data Analysis (EDA), statistical modeling, predictive analytics 4. Time Series Analysis: ARIMA modeling, correlation and trend analysis 5. Big Data and Distributed Systems: Apache Spark, Hadoop, Kafka, Databricks 6. Development and Integration: Django, Flask, Spring Boot, REST API, Telegram Bot API 7. Databases: PostgreSQL, MongoDB, Redis 8. DevOps and Cloud: Docker, Kubernetes, GitLab CI/CD, AWS, Microsoft Fabric 9. Visualization and BI: Power BI, Tableau, Plotly Dash, Streamlit Technical Skills * Programming Languages: Python, Java (Kotlin, Scala), C/C++, C#, R, SQL, JavaScript, Typescript(HTML/CSS) * ML/DL Frameworks: scikit-learn, TensorFlow, PyTorch, NumPy, Pandas, Matplotlib, Seaborn * Infrastructure: Docker, Docker Compose, GitLab Pipelines, Jenkins, Azure, AWS * Project Management: Jira, Confluence, Trello, Agile/Scrum * Cloud Platforms: Microsoft Fabric, Databricks, DigitalOcean Professional Approach Every project I take on is an opportunity to create something functional, elegant, and intellectually robust. My goal is not just to build technical solutions, but to design intelligent systems that bring measurable value to the business. I’m confident that any collaboration will be productive, efficient, and mutually beneficial — and that the results will exceed expectations.

I build practical Machine Learning models and Data Science solutions from data preprocessing to deployment in web applications. Built models trained on 5k–10k images, achieving ~85–90% accuracy on test datasets. Implemented end-to-end model deployment and integration, including feature preprocessing, API setup, and front-end visualization. My focus is on Computer Vision and Deep Learning projects, delivering solutions that work reliably in real-world environments. Skills: Tools/Frameworks: Python, TensorFlow (Keras), TensorFlow.js, Scikit-learn, OpenCV, Jupyter, ONNX ML & DL: Computer Vision, YOLO, Object detection, CNN, RNN, LSTM, Transformers Deployment & Integration: AWS, Azure, API integration, browser-based models Data Science & Analytics: Data Preprocessing, Data Collection, Feature Engineering, Exploratory Data Analysis (EDA), Data Visualization

Software Developer with experience in Machine Learning, mostly Computer Vision. Have been working with PyTorch, TensorFlow, OpenVino, TensorRT, ONNXRuntime and Scikit-learn, deployment through Docker, FastApi, Django, Flask, AWS, DeepStream. I have some experience in building desktop, web and mobile apps as well. The languages I know well are Python, C/C++, Java, SQL. In addition, I can do Data Analysis and Visualisation through Scikit-learn, Pandas, MySQL and Tableau.