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Senior
Регистрация: 10.11.2022

Максим Межов

Специализация: AI Engineer / Data Scientist
— I design and implement AI systems that solve practical problems — from industrial process automation to AI-assisted user interfaces. — My focus is on building solutions that actually work in production and deliver real value. — With 5+ years of experience in AI and Data Science, I’ve worked across two key domains: — Industrial AI — failure detection, fuzzy control systems, process optimization. — LLM-based applications — agentic systems, retrieval-augmented generation (RAG), multimodal assistants. Recent projects include: — A multimodal RAG system for personalized fashion recommendations. — A plant documentation assistant powered by locally hosted LLMs and custom embeddings. — ViGist – a tool that extracts key insights from long-form YouTube videos. — AI agents for automating interactions in education and services. — Winner of DigitalSkills-2021 in Machine Learning & Big Data. — Co-author of 3 research publications in AI. Publications: — Digital Skills 2021. — Using machine learning to determine accounting codes based on the economic rationale of procurement documentation. — Anomaly Detection in a Granulation Plant for Uranium Dioxide Powder Pressing into Fuel Pellets. — Machine Learning Model for Early Detection of COVID-19 by Heart Rhythm Abnormalities.
Data Scientists Python Microsoft SQL server Django Java MySQL scikit-learn Tensorflow Software Development FastAPI Автоматизация процессов Нейронные сети NumPy LLM Qdrant Machine Learning Deep Learning Алгоритмы RAG Artificial Intelligence
— I design and implement AI systems that solve practical problems — from industrial process automation to AI-assisted user interfaces. — My focus is on building solutions that actually work in production and deliver real value. — With 5+ years of experience in AI and Data Science, I’ve worked across two key domains: — Industrial AI — failure detection, fuzzy control systems, process optimization. — LLM-based applications — agentic systems, retrieval-augmented generation (RAG), multimodal assistants. Recent projects include: — A multimodal RAG system for personalized fashion recommendations. — A plant documentation assistant powered by locally hosted LLMs and custom embeddings. — ViGist – a tool that extracts key insights from long-form YouTube videos. — AI agents for automating interactions in education and services. — Winner of DigitalSkills-2021 in Machine Learning & Big Data. — Co-author of 3 research publications in AI. Publications: — Digital Skills 2021. — Using machine learning to determine accounting codes based on the economic rationale of procurement documentation. — Anomaly Detection in a Granulation Plant for Uranium Dioxide Powder Pressing into Fuel Pellets. — Machine Learning Model for Early Detection of COVID-19 by Heart Rhythm Abnormalities.
Data Scientists Python Microsoft SQL server Django Java MySQL scikit-learn Tensorflow Software Development FastAPI Автоматизация процессов Нейронные сети NumPy LLM Qdrant Machine Learning Deep Learning Алгоритмы RAG Artificial Intelligence

Портфолио

PJSC “MSZ” (Elemash)

Lead of Document Management team

Tsifrum (Cifrum)

Data Scientist

Digital Technologies and Platforms LLC

Data Scientist

Скиллы

Python
Microsoft SQL Server
Django
Java
MySQL
MyStem
Scikit-Learn
TensorFlow
LSTM
Machine learning
Data analysis
PyTorch
Time-Series
C#
Industrial AI
Process Automation
Fuzzy Logic

Опыт работы

Data Scientist
с 04.2024 - По настоящий момент |Taiga Dynamics
Python, Fuzzy Logic, FastAPI, NumPy, Qdrant, Custom Embeddings, Multimodal LLMs, Parallel Computing, Time Series Analysis.
● Building AI-driven systems with a focus on industrial automation, real-time control, and LLM-based retrieval systems. ● Hands-on experience with RAG architectures, fuzzy logic, and multimodal LLMs. Key Achievements: ● Context-aware assistant for plant documentation — Designed and implemented a custom Retrieval-Augmented Generation system, manually building a ColPali-style embedding architecture for hierarchical chunking and context preservation. Integrated with a locally hosted multimodal LLM to enable accurate question answering over technical and visual documents. ● Failure detection for flotation & grinding circuits — Developed a rule-based fault detection system using historical telemetry and parallel processing. Delivered an 8.37 percentage point improvement in equipment availability, boosting metal recovery (Ni, Cu, Co) by 10% during trials. ● Real-time fuzzy control for SAG mill & hydrocyclones — Built fuzzy controllers to automate SAG mill speed and hydrocyclone feedwater regulation. Resulted in a ≥30% improvement in stability of critical process parameters, reducing operator workload and enhancing system robustness. ● Mentorship & internal tooling — Supported junior team members and introduced reusable development workflows to accelerate iteration and deployment.
AI Engineer
02.2024 - 04.2025 |AI Startup
LLMs, Agentic Systems, Multimodal RAG, Python, OpenAI API, Hugging Face, LangChain, FastAPI, Flask, Telegram API, PostgreSQL, Docker, Celery, Qdrant, Multimodal Embeddings, Agentic Design Patterns
● Building and deploying AI-driven products using LLMs, AI-agent frameworks, and workflow-based automation. ● Focus on fast prototyping, user-centric tooling, and production-grade system integration. Key Projects: ● Multimodal RAG-based stylist assistant — Developed a Retrieval-Augmented Generation system combining text–image embeddings to match user-uploaded outfit photos with stylistically relevant products from a marketplace. Built an LLM-powered assistant that interprets visual input and returns style-consistent recommendations with live product links. ● AI agent for beauty service booking — Implemented a tool-using AI agent (function calling) to handle customer dialogs, check CRM availability, and schedule appointments in real time. ● AI-powered assistant for a coding school — Created a multi-step agent pipeline with parallelized evaluators and optimizers to qualify leads, personalize answers, and enroll students automatically. ● ViGist – YouTube video summarization assistant — Designed an agent framework that captures key insights and highlights from long-form videos. ● AI content curator for the Data Science community — Built a chained prompt-based workflow that autonomously curates, formats, and publishes daily digests.
Data Scientist
07.2022 - 04.2024 |EuroChem
MVP, ML
● Developed and implemented a minimum viable product (MVP) of a recommender system, utilizing three machine learning models to achieve a 12% boost in phosphoric acid production. ● Completed an end-to-end Proof of Concept (PoC) for an industrial data science project aimed at reducing methanol production costs.
Data Scientist
04.2020 - 06.2022 |Rosatom Global
ML, Python, Algorithms
● Reduced workflow time of the conformity assessment documents for products by 95% by creating a classification machine learning model. ● Automated a workflow process for detecting COVID-19 at an early stage using abnormalities in heart rhythm by creating a machine learning model which allows the detection of coronavirus in 83% of cases using data from mobile devices. ● Extended continuous operation period of a flame reactor by 30% by creating a machine learning model to anticipate clogging using time-series data from sensors. ● Sped up the procurement documentation classification process by 81% by developing a Streamlit-based Python web application using TF-IDF and classic machine learning algorithms.

Образование

Applied Mathematics and Computer Science; and an advanced degree in Mathematics Education (Магистр)
2004 - 2009
Ivanovo State Power Engineering University

Языки

АнглийскийВыше среднего