Position: Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 2

• Certificate about participating in the Final stage of IDAO (International Data Analysis Olympiad) held by Yandex LLC, Moscow. Top 30 among the 1000 teams.
• Award of Achievement for successfully completing the Oracle Academy "Database Design and Programming with SQL”.
• Deep Learning Specialization Certificate offered by Coursera, Deeplearning.AI
Machine Learning Engineer, master's student at the University of Padua, Italy in ICT.

I'm quite interested in working on images utilizing Computer Vision and Deep Learning. Currently, I'm conducting research about detecting anomalies in data coming from smart health devices using Machine Learning techniques.

Education:
- Bachelor's degree in Computer Engineering, ADA University, Baku, Azerbaijan.
- Master's degree in ICT, University of Padua, Italy.

Past experiences:
- Machine Learning Engineer
Desion GmBH, Darmstadt, Germany.
(November 2021 – June 2022)
• Utilizing Keras, Tensorflow, and Pytorch frameworks to build Deep Learning models.
• Solving Image Classification, Object Detection and Localization types of Computer Vision problems.
• Built a web scraper and scraped around 200k images from the various websites.
• Developed Python/Bash scripts to clean and manage the raw dataset, and transform it to COCO, Pascal VOC data formats.
• Utilized the Detectron2 framework for object detection tasks with two-stage architectures (Faster R-CNN, Mask R-CNN).
• Utilized the Keras framework for classification tasks with one-stage architectures (VGG, ResNet, EfficientNet).
• Implemented different techniques to evaluate the performance of the trained networks such as item similarity based on Top-N recommendation.
• Utilized KerasTuner and RayTuner hyperparameter search
frameworks for hyperparameter tuning. Deep dive into the Bayesian hyperparameter optimization.
• Set up and further improve the data pipeline, and implement data augmentation with Tensorflow Data API.
• Built a REST API using Flask that handles user login, registration, and authentication with JWTs, accepts images from the user side, and returns the model prediction 
• Read research papers about the novel network architectures and implemented them in Keras.
• Worked with SQL to manage the user-related data in REST API and embeddings from the trained networks over images for the recommendation system.

Software Engineer Intern
Mobisec Italia Srl, Treviso, Italy
(March 2021 – May 2021)
• Development of Automated Security Tool.
• Automation of the "Dry-run" process which checks the vulnerabilities present in the mobile application on a surface level.
• Utilizing Machine Learning to detect false/positive results from the "MobSF" platform.
• Applying Convolutional Neural Networks (CNNs) to automate the detection of UI fields.
• Using "Appium" to automate UI processes.