Dmytro K.
Senior AI/ML Engineer
Experience
May 2023 - Apr 2025
2 yearsCambridge, 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 yearsCambridge, 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 monthsTallinn, 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
IntermediateUkrainian
IntermediateEstonian
ElementaryEducation
Sep 2015 - Jun 2019
Bohdan Khmelnytsky University
Bachelor’s Degree in Computer Science · Computer Science · Ukraine
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