Viacheslav Zhenylenko, Machine Learning Developer in San Diego, United States
Viacheslav Zhenylenko

Machine Learning Developer in San Diego, United States

Member since May 12, 2019
Viacheslav has seven years of experience in data science and software engineering. He is passionate about the insights gained from raw data and enjoys converting them to create exceptional business value. His primary expertise is Python, with production experience in Java and C++. He has applied advanced machine learning techniques such as computer vision, NLP, product recommendation systems, networking data, and classical data science to solve data-heavy projects.
Viacheslav is now available for hire




San Diego, United States



Preferred Environment

Eclipse, VS Code, PyCharm, Jupyter, MacOS, Linux

The most amazing...

...project I've developed was an industry-first, self-reconfigurable AutoML system for congestion detection in RAN networks.


  • Lead Data Scientist

    2020 - 2022
    Botprise, Inc.
    • Developed the back end for the full ML cycle, ModelOps, and MLOps, on the platform.
    • Worked on dozens of automation use cases, including MLOps, analytics, DataOps, networks, ITOps, etc.
    • Created the back end and partial front end with React for a drag-n-drop chatbot building application.
    • Implemented and deployed dozens of algorithms (classification, clustering, time series, NLP, and computer vision) for different use cases.
    • Led a small ML team, including planning, management, monitoring, and leadership.
    Technologies: Amazon Web Services (AWS), Python, Flask, MongoDB, Apache Kafka, React Redux, REST, Docker, Kubernetes
  • Senior AI Developer

    2019 - 2020
    • Developed an ingestion and processing pipeline on AWS for photos from surveillance cameras.
    • Experimented with various non-DL and DL approaches and tested them. Trained and used the Siamese network with an attention mechanism, achieving 95%+ accuracy.
    • Created and shared presentations with analytics to executives. Developed and maintained a Wiki for the project.
    Technologies: Amazon Web Services (AWS), AWS, TensorFlow, Python, Docker
  • Team Lead

    2018 - 2019
    The National Academy of Sciences of Ukraine
    • Led and mentored a team of students. I defined objectives and controlled the process using the Agile methodology.
    • Created a tool for crops classification and map creation.
    • Collected data both manually, and via web scraping using Mapillary, and oversaw the data labeling.
    • Implemented and tested DeblurGAN and several other classic deblurring methods.
    • Oversaw field localization (YOLO) and crop classification by fine-tuning a ResNet model.
    Technologies: OpenCV, PyTorch, TensorFlow, Keras, Python
  • Senior Data Scientist

    2017 - 2019
    Openwave Mobility
    • Created a multi-staged data pipeline from raw packets data (TCP/IP layer) to consumable inputs for machine learning models with multi-processing implementation in Python (CPython).
    • Trained, tuned, evaluated and compared multiple machine learning models in Python (scikit-learn, Keras, XGBoost, CatBoost) and C++ (mlpack).
    • Oversaw the data analysis and communication with stakeholders. Created a reusable Python tool for rapid and externally configurable data analysis reports generation.
    • Implemented custom feature generation algorithms based on expert knowledge based on aggregation, derivatives, delays in TCP/IP conversation, products, and fractions.
    • Implemented custom multi-staged feature selection algorithms that were model based.
    • Deployed and monitored the project in production in the network. If the tool detects congestion, optimization policies were applied. Customers reported up to a 20% increase of quality of delivery for video content.
    Technologies: C++, Python
  • Data Scientist

    2015 - 2017
    • Developed, deployed, and evaluated a hybrid recommendation engine in Python for an online store.
    • Oversaw customer behavior analysis, visualization, and stakeholder communication.
    • Handled different scenarios of user engagement using a strategy pattern. Contextual recommendations were given based on popularity (general and category-based), item-to-item, and SVD. (Python, scikit-learn, SciPy). The system was integrated into a Django website.
    • Conducted multiple A/B tests with random sampling for evaluation of the system. Compared to the most popular items in the category baseline, we achieved up to a 150% boost in purchases-per-session, and increase of revenue.
    • Created an image super-resolution module for an online Cloud site constructor with Keras.
    • Utilized middle-deep CNN, trained on several blur kernels, and deployed it as a service via REST.
    • Conducted surveys showing an increase of about 5% in the satisfaction for users of the platform.
    Technologies: TensorFlow, Keras, Python
  • Software Engineer Intern

    2015 - 2015
    • Trained and evaluated AdaBoost models for customer churn prediction using FBLearner Flow.
    • Performed hyper-parameters tuning for optimization.
    • Data engineered with Hive and processed data using Python.
    Technologies: Apache Hive, Python
  • Researcher Intern

    2014 - 2015
    • Developed algorithms for smart keyboard functionality (word prediction and spelling correction).
    • Developed Naive Bayes for n-grams, and K-Nearest Neighbors (KNN) for spelling corrections.
    • Created tweaks for better algorithm performance using Laplace smoothing and a custom keyboard distance for KNN.
    • Developed algorithms with C++. Integrated them with a Java to Android keyboard and published to the App Store.
    Technologies: C++, Android, Java
  • Software Engineer Intern

    2013 - 2014
    Engage Point
    • Developed a Content Management Interoperability System in Java EE. I used the Model View Controller framework for the application.
    • Developed Enterprise Java Beans for the business logic of the application.
    • Developed JavaServer Pages for the presentation level.
    Technologies: Java EE


  • Languages

    Python, SQL, Fortran, Java, C++, R
  • Libraries/APIs

    Scikit-learn, Keras, TensorFlow, PyTorch, Pandas, NumPy, OpenCV, React Redux
  • Tools

    IPython Notebook, Apache Airflow, Git, Jupyter, PyCharm, VS Code
  • Paradigms

    Data Science, Agile Software Development, Parallel Programming, REST
  • Other

    Predictive Analytics, Predictive Modeling, Computer Vision, Data Analytics, Deep Learning, Machine Learning, Mathematics, Applied Mathematics, Statistics, Algorithms, AWS, GCP, Machine Learning Automation, Recommendation Systems, Natural Language Processing (NLP), Science, Scientific Computing
  • Platforms

    Amazon Web Services (AWS), Linux, Kubernetes, MacOS, Eclipse, Android, Java EE, Apache Kafka, Docker
  • Storage

    MySQL, Apache Hive, MongoDB
  • Frameworks

    Django, Flask


  • Master's Degree in Theoretical Physics (Quantum Field Theory)
    2019 - 2021
    Kyiv National University - Kyiv, Ukraine
  • Master's Degree in Computer Mathematics and Algebra
    2018 - 2020
    Kyiv National University - Kiev, Ukraine
  • Bachelor's Degree in Computer Science and Applied Statistics
    2010 - 2014
    Kyiv National University - Kiev, Ukraine


  • Data Science: Data to Insights
    MAY 2017 - PRESENT
    Massachusetts Institute of Technology (MITx)
  • CSMM.101x: Artificial Intelligence (AI)
  • 2nd Place
    MAY 2011 - PRESENT
    ACM-ICPC, Country level
  • Bronze Medal
    JULY 2010 - PRESENT
    International Mathematical Olympiad (IMO)
  • 2nd Place
    MAY 2009 - PRESENT
    Kyiv International Physics Festival

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