Вероніка

VERONIKA PAVLIUK
Kyiv, Ukraine (open to remote) · [відкрити контакти](див. вище в блоці «контактна інформація») · [відкрити контакти](див. вище в блоці «контактна інформація») ·

github.com/ronnyasha · [відкрити контакти](див. вище в блоці «контактна інформація»)

SUMMARY
4th-year Information Systems student (KPI) with hands-on, project-based experience across the full AI/ML stack —
classical machine learning, deep learning (CNN/RNN/transfer learning), computer vision, and cloud/DevOps
infrastructure. Built a real-time object detection system (YOLOv11, mAP50 0.995) and deployed cloud
infrastructure with Docker, AWS, and Terraform. Seeking a Junior AI / Computer Vision / ML or DevOps role.

TECHNICAL SKILLS
Languages: Python, Java, SQL
Machine Learning / DL: TensorFlow, Keras, PyTorch, scikit-learn, Scikit-Fuzzy
Computer Vision: OpenCV, YOLOv11 (Ultralytics), Albumentations, Roboflow
Data Analysis: NumPy, Pandas, SciPy, Matplotlib, Seaborn
Cloud & DevOps: Docker, AWS (EC2, IAM), Terraform, GitHub Actions (CI/CD), Prometheus, Grafana,
RabbitMQ, Vagrant, Linux, Git

SELECTED PROJECTS
Custom Object Detection with YOLOv11 Python · YOLOv11 · OpenCV · Albumentations
● Built a real-time object detection system trained on a custom dataset, using smart auto-labeling via
Roboflow + SAM 3
● Achieved mAP50 of 0.995 (Precision/Recall ~1.0) with ~25–30ms/frame inference speed on video
Cloud & DevOps Infrastructure Labs Docker · AWS · Terraform · GitHub Actions · Prometheus · Grafana
● Deployed containerized applications to AWS EC2 and automated infrastructure provisioning with Terraform
(IaC)
● Built a CI/CD pipeline (GitHub Actions + Watchtower) for automated build, push, and deployment on
commit
● Set up monitoring and logging stacks (Prometheus/Grafana, EFK) and an event-driven messaging system
with RabbitMQ
Neural Network Architectures Python · TensorFlow/Keras · PyTorch · OpenCV
● Implemented and trained MLP, CNN, and RNN/LSTM models, plus transfer learning with AlexNet,
InceptionV3, and Xception
● Built a sentiment analysis model (LSTM) reaching 87% accuracy on the Yelp Reviews dataset
Data Analysis with Python Python · Pandas · NumPy · scikit-learn
● Built end-to-end data analysis pipelines: statistical hypothesis testing, time series analysis, and data cleaning
● Developed regression, classification, and clustering models with scikit-learn, tuned via GridSearchCV and
PCA

EDUCATION
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
B.Sc. in Information Systems and Technologies (126), Faculty of Informatics and Computer Science (FICT) — 4th
year, expected graduation 2027

LANGUAGES
Ukrainian: Native
English: Advanced
Polish: Upper-intermediate