Dmytro K.

Senior AI/ML Engineer

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Pärnu, Estonia

Experience

May 2023 - Apr 2025
2 years
Cambridge, United States

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.
May 2021 - Apr 2023
2 years
Cambridge, United States

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.
Oct 2019 - Mar 2021
1 year 6 months
Tallinn, Estonia

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.

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

English
Intermediate
Ukrainian
Intermediate
Estonian
Elementary

Education

Sep 2015 - Jun 2019

Bohdan Khmelnytsky University

Bachelor’s Degree in Computer Science · Computer Science · Ukraine

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