Aleksandar Loncar, Image Recognition Developer in Novi Sad, Vojvodina, Serbia
Aleksandar Loncar

Image Recognition Developer in Novi Sad, Vojvodina, Serbia

Member since September 23, 2019
Aleksandar is a machine learning engineer and a passionate mathematician and algorithm engineer with strong analytical and problem-solving skills. He started as a software engineer and, over the years, found himself in the data science field, especially in deep learning and AI.
Aleksandar is now available for hire


  • TickUp
    Python, Data Science, Machine Learning, Forecasting, Time Series Analysis...
  • Symphony
    Computer Vision, Image Recognition, AWS, Amazon SageMaker, Keras, TensorFlow...
  • Symphony
    Amazon SageMaker, Machine Learning, Computer Vision, Image Recognition, AWS...



Novi Sad, Vojvodina, Serbia



Preferred Environment

Git, Linux, Windows, MacOS, Jupyter

The most amazing...

...projects I've fulfilled are creating new or adjusting algorithms for some non trivial problem.


  • Data Scientist | Quant Researcher

    2021 - 2021
    • Created models for forecasting time series, performed research on machine learning approaches in the field, time-series trend changes analysis and modeling, and more.
    • Analyzed several data, performed data quality checks, and cleaned pipelines.
    • Operated on datasets provided by Bloomberg and similar providers.
    Technologies: Python, Data Science, Machine Learning, Forecasting, Time Series Analysis, Data Analysis
  • Machine Learning Engineer

    2021 - 2021
    • Developed a machine learning solution that can find forest edges from satellite imagery.
    • Worked as a machine learning engineer on this project, responsible for the R&D process. Analyzed data sources and organized training and inference pipelines for machine learning models in cloud environments.
    • Delivered state-of-the-art solution for the selected computer vision problems.
    Technologies: Computer Vision, Image Recognition, AWS, Amazon SageMaker, Keras, TensorFlow, Python, Jupyter, Machine Learning
  • Machine Learning Engineer

    2020 - 2021
    • Developed a machine learning solution that can estimate building roof attributes (predominant pitch, eave height, story count) from (synthetic) point cloud data and areal imagery.
    • Worked as a team lead and machine learning engineer on this project, responsible for the R&D process.
    • Analyzed data sources and applied classical algorithms from computer vision and Point cloud domains, and machine learning algorithms.
    • Conducted experiments to find the best fitting ML solutions for ML classification and regression models. He also experimented with custom loss functions and data pre-processing based on recent papers.
    Technologies: Amazon SageMaker, Machine Learning, Computer Vision, Image Recognition, AWS, Python, Jupyter, Keras, TensorFlow, Point Clouds
  • Data Scientist | Full-stack Developer

    2020 - 2021
    • Created a system that forecasts future sales based on historical data—time series analysis. The system is used for internal purposes.
    • Developed a web application that allows users to upload historical data (sale data, inventory data, and more), list top-selling items, view trends per warehouse, and make forecasts for future periods.
    • Built a system that optimizes warehouse management.
    Technologies: Data Science, Python, AWS, Flask, Time Series, Sales Forecasting, Time Series Analysis
  • Machine Learning Engineer | Computer Vision

    2020 - 2020
    Faculty of Transportation Sciences (via Toptal)
    • Developed a PoC drone traffic analysis based on computer vision and deep learning algorithms.
    • Researched SotA approaches (papers and solutions) for object detection and object tracking based on video from an aerial perspective: Surveillance cameras, drones/planes, and satellites.
    • Found suitable train datasets for the use case and trained object detectors in AWS cloud.
    Technologies: Machine Learning, AWS, Amazon SageMaker, Computer Vision, TensorFlow, PyTorch, Python, Deep Learning, Image Recognition
  • Computer Vision R&D Engineer | Team Leader

    2019 - 2020
    • Developed computer vision and deep learning algorithms.
    • Led the analytics team. Worked on computer vision and ML/data science solutions for ADAS (advanced driver assist systems) validation and analyzed terabytes of test drive data.
    • Scaled up ML and other software solutions in the cloud environment(s).
    Technologies: Google Cloud Platform (GCP), Keras, TensorFlow, Python, Machine Learning, Data Science, Artificial Intelligence (AI)
  • Senior Software Engineer, Machine Learning Engineer

    2015 - 2019
    • Developed full-stack machine learning pipelines for both a training and production environment in Python.
    • Involved in the development of a face recognition system based on deep learning: A machine learning project developed on the TensorFlow framework.
    • Developed a machine learning model based on transfer learning for leaf counting (plant phenotyping).
    • Developed many regression and classification models for tabular data.
    • Maintained, optimized, and developed some features in a voice authentication system. Responsible for the SIP proxy app that bridges incompatibility between the PBX and their SIP stack.
    Technologies: Redis, .NET, C++, Keras, TensorFlow, C#, Python, Azure, Data Science, Machine Learning, Computer Vision
  • Data Scientist

    2017 - 2018
    Brisqq LTD
    • Performed time series analysis and forecasting.
    • Participated in courier tiers optimization.
    • Developed model for next delivery prediction, time and geo-location. Part of the recommendation system for couriers.
    • Performed geo-location clustering based on data history.
    • Made a model that classifies couriers based on their performances.
    Technologies: MongoDB, Keras, TensorFlow, Python
  • Senior Software Developer, Development Team Leader

    2014 - 2015
    • Tasked with making enterprise cloud-based software solutions for medical practices and other entities in the domain of healthcare.
    • Developed enterprise software architectures with multi-tenant database models.
    • Led a team of 6+ members, coordinated between UI/UX designers, front-end and back-end devs, and other participants.
    Technologies: Elasticsearch, MySQL, Microsoft SQL Server, Angular, ASP.NET
  • Software Developer

    2012 - 2014
    • Developed custom web applications.
    Technologies: MySQL, Microsoft SQL Server, C#, ASP.NET


  • Couriers Delivery Forecasting System

    A recommendation system for couriers based on machine learning models that can predict the next delivery in spatial grid and time, based on historical data.

  • Face Recognition System

    Face Recognition system is a PoC based on deep learning. Users can create profiles on the system, the number of required images for the profile can vary and depend on configuration. Next step is that the user can verify new image against the enrolled profile. The system is set to minimize false positive rate, and prevent impostors to verify as registered users. It can also execute identification against all enrolled users.

    Because it is trained on best-known datasets, it is very robust to illuminance, image blur, head pose variation, gender, and ethnicity.

  • Warehouse Sales Forecasting System

    A Python-based web application for warehouse management optimization.
    I was a full-stack developer and a data scientist. The core of the system is a machine learning model that forecasts sales per warehouse, it consumes historical sales and inventory levels data. The app has rich data visualizations (graphs and trends) and role-based access control, deployed in AWS.


  • Languages

    Python, C#, C++
  • Libraries/APIs

    Keras, PyTorch, TensorFlow, Pandas
  • Tools

    Amazon SageMaker, Jupyter, Git
  • Paradigms

    Data Science
  • Other

    Artificial Intelligence (AI), Amazon Machine Learning, Google Cloud Machine Learning, Image Recognition, Time Series, Time Series Analysis, Machine Learning, Deep Learning, Computer Vision, Forecasting, Data Analysis, AWS, Sales Forecasting, Point Clouds
  • Storage

    MySQL, Redis, Microsoft SQL Server, Elasticsearch, MongoDB
  • Frameworks

    ASP.NET, Angular, .NET, Flask
  • Platforms

    Windows, Linux, Google Cloud Platform (GCP), Azure, MacOS, Docker


  • Master's Degree in Computer Science
    2012 - 2014
    University of Novi Sad - Novi Sad, Serbia
  • Bachelor's Degree in Computer Science
    2007 - 2011
    University of Novi Sad - Novi Sad, Serbia


  • Deep Learning Specialization
  • Convolutional Neural Networks
  • Sequence Models
  • Neural Networks and Deep Learning
  • Structuring Machine Learning Projects
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

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