Володимир

Volodymyr Borysiuk
Senior Python Developer
[открыть контакты](см. выше в блоке «контактная информация») | [открыть контакты](см. выше в блоке «контактная информация») | Ukraine

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More than 6 years of experience in designing, developing, LinkedIn:
testing, and maintaining cloud-based micro-services, [открыть контакты](см. выше в блоке «контактная информация»)
borysiuk-64b1621b5/
application design patterns & approaches, cloud
architecture patterns, and refactoring techniques. PyPi:
https://pypi.org/user/volodymyrb/
Was responsible for the development of application
servers, event-based scripts, data pipelines, automation
processes, automatic report generation, and web
applications. Skills
Able to effectively self-manage during independent Python 4/5
projects, as well as collaborate in a team setting. Have FastAPI 4/5
experience in mentoring and sharing experiences. Always asyncio 4/5
help my colleagues if they have difficulties. Ready for Flask / Django / DRF 3/5
stressful situations. GCP / AWS 3/5
Microservices 4/5
Docker / Compose 3/5
SQL / NoSQL 4/5
Employment History Git / GitHub / Bitbucket 4/5
JS / Dart 3/5
Senior Software Engineer at Fornova, Remote ML / DS 2/5

07/2023 — Present
Team: AI / ML
• Dev: 7
Computer Vision 3/5
• DevOps: 3
OpenCV 3/5
• QA: 5
Keras / TensorFlow 3/5
• Customer Support: 5 PyTorch (learning) 2/5
Tools: Deep Learning (CNN) 3/5
PyCharm, Postman, VPN, DataGrip, Docker Desktop, FileZilla, NumPy / pandas 3/5
Lens scikit-learn 3/5

Technologies:
Micro-services, REST API, RabbitMQ, SQS, PostgreSQL, MySQL,
Redshift, MongoDB, Cassandra, GCP (Storage, Pub/Sub, Airflow,
Kubernetes, Cloud Functions, Memory Storage), Jenkins, Docker,
Docker Compose, asyncio, FastAPI, Git, Bitbucket, Coralogix, Languages
Redis, OpenTelemetry. English Highly proficient
Participation: Ukrainian Native speaker
• Conduct interviews and participate in the selection process
for candidates.
• Support existing micro-services.
Hobbies
• Develop a message-broker-based services.
• Develop automated reports using Airflow. Computer games, board games

• Added execution performance monitoring to a legacy high-
load service for a major customer, enabling detection of
performance bottlenecks. The monitoring stack is based on
OpenTelemetry and Coralogix.
• Designed and implemented a public REST API that receives
hotel rates and generates data feeds for advertising
channels, including Google, Trivago, TripAdvisor, and Bing.
Performed extensive performance optimizations to ensure
fast and reliable data delivery.
• Develop an internal web application to manage and monitor
the micro-services stack, using FastAPI, MongoDB, Jinja2,
HTMX, and Bulma. The main goal of this web application was
to transfer responsibility for managing customer
configurations, parameters, and limits from developers to
the Customer Support team. It eliminated the need to
modify configurations directly in MongoDB and provided an
intuitive interface for managing them.
• Develope microservice that detect anomalies in data based
on rules.

Senior Software Engineer at Epam Systems, Vinnytsya

07/2022 — 07/2023
Team:
• Dev / DevOps Team: 6
• BI Team: 4
Tools:
PyCharm, Postman, VPN, DataGrip, Docker Desktop
Technologies:
Data Warehouse, dbt, REST API, Airflow, Snowflake, Redshift,
MySQL, AWS (SQS, Cloud Build), GitHub.
Participation:
• Led the Ukrainian part of the team of three developers
(including myself).
• Conducted interviews and participated in the candidate
selection process.
• Manage tickets for the legacy Data Warehouse.
• Monitor and support the legacy Data Warehouse.
• Participate in developing a new Data Warehouse.

Python Developer at Pillar - Solid Offshore, Vinnytsia

05/2019 — 07/2022
Team:
• Dev Team: 7 members
• QA Team: 4 members
• DevOps Team: 2 members
Tools:
PyCharm, Postman, VPN, DataGrip, Docker Desktop, FileZilla,
Jupyter Notebook
Technologies:
Micro-services, REST API, RabbitMQ, SQS, Pub/Sub, PostgreSQL,
MySQL, MongoDB, Cassandra, CLI, AWS, GCP, Kubernetes,
Jenkins, Docker, Docker Compose, asyncio, Flask, FastAPI, Git,
Bitbucket, Coralogix, Redis.
Participation:
• Maintained and expanded a website scraping service that
could be scaled with threads.
• Developed REST API for an existing service that previously
worked only on the basis of SQS / RMQ.
• Actively participated in the development of a framework for
writing pipelines for data processing. Pipelines were mainly
used for streaming data and generating/sending reports.
• Developed CLI to facilitate testing and support the existing
services.
• Developed a public REST API for receiving requests from
customers. API processes a large number of requests. The
service has many different limits for input data, works on
HTTPS, and uses JWT for authorization.
• Developed a service based on a message broker. The service
transforms the data based on configurations.
 • Developed a service based on a message broker. The service
routes messages to the destination based on rules.
• Developed internal REST API for configuration management
for other services and creation of internal reports.
• Developed algorithm for sorting CSV files using disk space
and minimum RAM.
• Wrote unit tests.
• Wrote documentation for developed services.
• Code review and refactoring.
• Supported existing services.
• Had mentor experience.

AI / ML & Computer Vision Projects
Self-driven and academic R&D projects exploring deep learning,
computer vision, and recommender systems. Built with a
production-oriented mindset (modular code, tested,
documented) rather than notebook-only experiments.

Real-Time Facial Emotion Recognition at University,
Computer Vision

Technologies:
Python, OpenCV, Keras / TensorFlow, NumPy, Flask, WebSocket.
Participation:
• Built an end-to-end CV pipeline: face detection with
OpenCV, followed by a CNN classifier (Keras) predicting
facial emotion classes from cropped faces.
• Implemented real-time per-frame inference on a live video
stream and streamed results to the browser over
WebSocket; Flask backend serves the UI and wraps the
model.
• Addressed production concerns: frame batching, FPS-aware
throttling, model warm-up, and graceful client reconnection.

Neural Style Transfer at University, Deep Learning

Technologies:
Python, Keras / TensorFlow, NumPy, Pillow.
Participation:
 • Implemented neural style transfer on top of a pre-trained
deep CNN backbone (VGG-style feature extractor),
combining content and style (Gram-matrix) losses.
• Tuned optimizer settings, layer weights, and total-variation
regularization to balance stylization quality vs. structural
preservation.
• Wrapped the pipeline in a small reproducible CLI for batch
generation.

Movie Recommendation System at University, Machine
Learning

Technologies:
Python, NumPy, pandas, scikit-learn.
Participation:
• Built a recommender combining collaborative-filtering and
content-based approaches; trained, evaluated, and
compared models on standard offline metrics.
• Designed the data pipeline (ingestion → feature engineering
→ training → serving), keeping the same project structure
used in production microservices.

Education
PhD studies — Vinnytsia National Technical University,
Vinnytsya
05/2022 — Present

Master, Computer Science — Vinnytsia National Technical
University, Vinnytsia
08/2021 — 12/2022

Bachelor, Computer Science — Vinnytsia National Technical
University, Vinnytsia
Graduated 08/2021

Extra-curricular Activities

Fullstack Developer at Hagenboard.com, Vinnytsia

04/2022 — 06/2023
(Pet project for a real customer) Website / mobile development
for Hagenboard.com.
App requirements:
• Review of products and projects
• Admin panel
• E-commerce
• Product page editor
Stack:
• Python / FastAPI
• Dart / Flutter
• MongoDB
• GCP Cloud Run
• Firebase FileStorage
• Firebase Hosting