Dmytro Korchevnyi
Senior AI/ML Engineer
Experience
Senior AI/ML Engineer
ReversingLabs
- Lead the design and deployment of AI-driven solutions, focusing on scalable machine learning models for real-time analytics and automation.
- Developed and optimized deep learning models (CNNs, Transformers, LLMs) using PyTorch and TensorFlow, improving accuracy and efficiency across multiple projects.
- Built end-to-end ML pipelines—from data ingestion and feature engineering to model training, validation, deployment, and monitoring.
- Designed and deployed microservices for AI inference using FastAPI, Docker, and AWS/GCP, ensuring scalability and low latency.
- Applied MLOps practices such as automated retraining, model versioning, and CI/CD pipelines using MLflow, Airflow, and Kubernetes.
- Mentored junior data scientists and ML engineers, conducted code reviews, and helped establish best practices for reproducible and maintainable AI development.
- Collaborated with product and data engineering teams to integrate AI capabilities into existing systems, delivering measurable business impact.
- Researched and implemented advanced AI techniques (LLMs, generative models, and vector databases) to drive innovation and improve system intelligence.
- Spearheaded the deployment of an NLP-based automation model that reduced manual processing time by 40% and improved response accuracy by 30%.
- Designed a scalable inference architecture that cut model latency by 45%, enabling real-time decision-making in production environments.
- Implemented MLOps automation that reduced deployment time by 60% and improved model reproducibility.
- Led a cross-functional AI initiative that delivered a 15% increase in operational efficiency, recognized by senior leadership.
Data Scientist
ReversingLabs
- Supported data science initiatives focused on cybersecurity analytics, working with large-scale malware and threat intelligence datasets.
- Performed data cleaning, transformation, and feature engineering using Python, Pandas, and SQL to prepare structured datasets for model training.
- Assisted senior data scientists in developing machine learning models for anomaly detection, threat classification, and predictive analysis.
- Conducted exploratory data analysis (EDA) to uncover trends and improve model accuracy through better feature selection.
- Contributed to model evaluation and testing, using metrics like precision, recall, F1-score, and ROC-AUC.
- Created visualizations and reports in Matplotlib and Seaborn to communicate insights and findings to the analytics and engineering teams.
- Collaborated in cross-functional meetings to bridge the gap between data insights and real-world cybersecurity product enhancements.
- Helped improve malware detection accuracy by 18% through optimized data preprocessing and feature engineering techniques.
- Built internal tools to automate dataset validation, reducing manual data preparation time by 25%.
- Gained hands-on experience in AI and machine learning workflows, contributing to applied research on predictive threat modeling.
Junior Data Scientist
MindTitan
- Assisted in data collection, cleaning, and preprocessing from multiple sources to ensure high-quality datasets for analytics and modeling.
- Conducted exploratory data analysis (EDA) to identify trends, patterns, and anomalies, supporting decision-making for business teams.
- Developed predictive models using Python and scikit-learn for customer behavior.
- Built data visualizations and dashboards using Matplotlib, Seaborn, and Tableau to communicate insights to stakeholders.
- Collaborated with senior data scientists and engineers to support model deployment and data pipeline optimization.
- Documented workflows and analysis to ensure reproducibility and maintain best practices in data handling.
- Improved data preprocessing efficiency by 20% by implementing automated scripts.
- Contributed to a predictive model that increased forecast accuracy by 15%, assisting the business in better planning.
- Participated in cross-functional projects involving AI and NLP, gaining exposure to real-world machine learning applications.
Industries Experience
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Experienced in Information Technology (5.5 years) and Professional Services (1.5 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Research and Development (4 years), Information Technology (3.5 years), Business Intelligence (3.5 years), and Product Development (2 years).
Summary
Data Scientist & AI Engineer with 6+ years of experience in developing and deploying machine learning and deep learning solutions. Strong expertise in Python, TensorFlow, PyTorch, and MLOps, with a proven record of building scalable AI systems for NLP, computer vision, and predictive analytics. Combines data-driven insight with engineering precision to deliver impactful, production-ready AI solutions that drive business value and innovation.
Skills
- Python
- R
- Sql
- Pandas
- Numpy
- Scikit-learn
- Tensorflow
- Pytorch
- Keras
- Hugging Face Transformers
- Opencv
- Spacy
- Langchain
- Nltk
- Matplotlib
- Seaborn
- Plotly
- Fastapi
- Flask
- Docker
- Kubernetes
- Mlflow
- Airflow
- Aws
- Gcp
- Deep Learning
- Nlp
- Computer Vision
- Mlops
Languages
Education
Bohdan Khmelnytsky University
Bachelor’s Degree in Computer Science · Computer Science · Ukraine
Profile
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