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TALENT-67171
Konstantin
Machine Learning Engineer
Armenia
Seniority
Middle
Language skills
English B1
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Skills
Industry
Professional Summary
Candidate with over 3 years of experience in data science and machine learning, specializing in NLP, LLMs, RAG systems, cloud services, and IoT devices. In the last two years, expertise has focused on NLP techniques, including LLM and RAG development, working with various vector databases, Snowflake, and cloud platforms like AWS and Azure. Experienced in MLOps, object detection, and deploying machine learning models on IoT devices. Proven track record in classic ML with tabular data and applying Git best practices in data science projects. Skilled in creating reproducible AI project repositories and conducting research using Jupyter notebooks. Previously worked as a design engineer, developing Python projects to optimize AutoCAD tasks.
Video of Talent
Portfolio
Education
Saint Petersburg State Marine Technical University / Specialist degree, Computers, complexes, systems and networks
2008 - 2013
Certifications and Trainings
Experience
Machine Learning Engineer
Self-employed
Aug 2024 - Present
Data Scientist
Industry: Software Development
Jan 2024 - Aug 2024
Developed a system for recommending correct MedDRA terms using open-source and proprietary LLMs (GPT, Llama), RAG, various vectorizers, prompt engineering, and infrastructure tasks, while working with Snowflake databases.
Conducted research on the application of transformers to predict specific diseases in patients based on sequences of text ICD codes, utilizing Snowflake databases.
Data Scientist
Industry: IT Services and IT Consulting
Apr 2021 - Dec 2023
Developed three LLM-based projects, including an AI math tutor, presentation summarizer, and support helper for tasks like document search, summarization, and RAG, using vector databases and Azure services.
Contributed to creating internal job position profiles, solving clustering and ranking tasks, and calculating employee matching scores with NLP and ML algorithms.
Built a cloud-based fraud detection system using AWS, Docker-compose, Mlflow for experiment tracking, and DVC for data versioning.
Led a project to predict employment status for 50,000+ employees, transitioning to CatBoost multiclass classification, expanding features, and improving CI/CD with Argo and BigQuery migration.
Designed a neural network for IoT device object detection using TensorFlow Object Detection API, integrating with backend systems for low-performance IoT devices with AWS services.
Improved a CV model’s performance using RedisAI and TFLite for object detection and classification, managing Docker containers and tracking experiments with Mlflow.
Projects
Project 1:
Applying ML in AutoCAD drawings, developed to speed up routine time-consuming operations and used for practicing MLOps practices.
Project 2:
Create a device for measuring filament thickness in manufacturing using OpenCV. Mechanical gauges have a number of problems that can be solved with a camera-based device. An application with a user interface was written in Python for this purpose, and a device prototype was assembled.
Project 3:
Use LoRa for open-source LLM fine-tuning on personal text data to simulate text behavior.
