Summary
Olga Chernytska is a Machine Learning Engineer with 9 years of experience specializing in computer vision and deep learning for manufacturing and industrial inspection. She has delivered production-ready object detection, defect detection, and image-alignment solutions using YOLO, PyTorch, OpenCV and edge-friendly model architectures, and has operationalized evaluation pipelines, experiment tracking (Weights & Biases) and AWS SageMaker deployments. Her background spans unsupervised and supervised methods—from fast, real-time anomaly detectors trained on unlabeled data to lightweight transfer-learned classifiers for small datasets—reflecting a pragmatic focus on accuracy, speed, and deployability. Olga pairs advanced technical work with strong data engineering and MLOps practices, having set up offline evaluation, metric calculation and automatic error analysis at scale. Based in Lower Silesia, Poland, she combines academic training in computer science and economics with hands-on startup and enterprise experience, often solving messy production data problems that research papers don’t cover.
9 years of coding experience
7 years of employment as a software developer
Master's degree Computer Science / Data Science, Master's degree Computer Science / Data Science at Ukrainian Catholic University
Master's degree Economic Analysis, Master's degree Economic Analysis at Kyiv School of Economics
Bachelor's degree Finance, Bachelor's degree Finance at Kyiv National Economics University