Alex T.

Machine Learning Engineer

Alex has a Ph.D. in Machine learning and has more than 7 years of professional experience in ML and computer science.

He has worked as a Machine learning engineer at companies such as Bosch and Samsung with use cases within computer vision and deep learning.

Main expertise
  • Python
    Python 7 years
  • C++
    C++ 3 years
  • Apache Kafka
    Apache Kafka 2 years
Other skills
  • NumPy
    NumPy 7 years
  • Machine learning
    Machine learning 6 years
  • TensorFlow
    TensorFlow 4 years
Alex
Alex T.
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Selected experience

Employment

  • Senior Machine Learning Engineer

    Virtual Control - 2 years

    • Development of a computer vision solution for shipments tracking in the supply chain.
    • Development of a human pose estimation algorithm based on deep learning technologies.
    • Development of human detection, one-camera tracking, multi-camera tracking, re-identification algorithm.
    • Increased accuracy of initial open source solution by 26% and inference time was decreased by 50%.
    • Designed architecture of the computer vision solution.
    • Improved speed of the system from 1 frame-per-second to 10 frames-per-second on 4 CPUs(without GPU usage) without loss in accuracy.
    • Led a team of the three ML and Software engineers in the project.

    Technologies:

    • Technologies:
    • NumPy NumPy
    • Python Python
    • Caffe Caffe
    • C++ C++
    • Kotlin Kotlin
    • OpenCV OpenCV
    • TensorFlow TensorFlow
    • Openvino Openvino
    • Kubeflow Kubeflow
  • Senior Software Engineer

    Occipital - 10 months

    • Development of ROS and ROS2 drivers for RGB-D camera.

    Technologies:

    • Technologies:
    • C++ C++
  • Senior Machine Learning Engineer

    Samsung R&D Institute - 1 year 3 months

    • Development of simultaneous localization and mapping (SLAM) algorithm for an autonomous vehicle.
    • Development of an object-detection algorithm for an autonomous vehicle based on deep learning technologies.
    • Development of traffic signs recognition algorithm for an autonomous vehicle based on deep learning technologies.
    • Improved accuracy of the initial open source solution by 5% by fusion of camera and lidar data.
    • Improved accuracy of the initial open source solution by 20% and inference speed was decreased by 30% by redesign of Neural Network architecture and improved training strategy.

    Technologies:

    • Technologies:
    • NumPy NumPy
    • Python Python
    • Caffe Caffe
    • C++ C++
    • Keras Keras
    • OpenCV OpenCV
    • TensorFlow TensorFlow
  • Machine Learning Engineer

    PrivatBank - 7 months

    • Development of a computer vision solution for an automatic line of people detection and counting.

    Technologies:

    • Technologies:
    • NumPy NumPy
    • Python Python
    • Caffe Caffe
    • XGBoost XGBoost
  • Software Engineer

    LightIt - 10 months

    • Development of a web-application with data analytics tools.

    Technologies:

    • Technologies:
    • Python Python
  • Mathematical Engineer

    JSC Zaporizhstal - 1 year 9 months

    • Development of a model of gas recirculation in sintering furnace and its implementation in the controller.
    • Development of a system for information gathering about all expenses of resources in a plant.

    Technologies:

    • Technologies:
    • Python Python
    • SQL SQL
    • MSSQL MSSQL
    • C++ C++

Education

  • Doctor Of PhilosophyMachine learning

    Taras Shevchenko National University of Kyiv · 2018 - 2022

  • MSc.Machine Learning

    Taras Shevchenko National University of Kyiv · 2012 - 2014

  • BSc.Automatization and Computer-Integrated Technologies

    Zaporizhia State Engineering Academy · 2008 - 2012

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