Serhii Shatov, Developer in Kiev, Ukraine
Serhii is available for hire
Hire Serhii

Serhii Shatov

Verified Expert  in Engineering

Machine Learning Developer

Kiev, Ukraine
Toptal Member Since
November 5, 2021

Serhii is a highly motivated and passionate data engineer who builds data-driven software products using demonstrated expertise in end-to-end software design and delivery. He has a multidisciplinary background, a proactive attitude and thrives in collaborative, team-oriented, and ambitious environments. Serhii is looking for challenging projects to apply his proven ability to drive the product from its inception to launch.


Let's Enhance
Triton Compute, Python, TensorFlow, PyTorch, PostgreSQL, ClickHouse...
Smart Home Solutions
Flutter, iOS, Android, KiCad, Autodesk Fusion 360, CNC Routers, PCB Design
Python, Deployment, Android, iOS, RabbitMQ, Redis, PostgreSQL, Machine Learning...




Preferred Environment

MacOS, Linux, PyCharm, Vim Text Editor, Slack

The most amazing...

...product I've developed is a machine-learning platform that serves more than 40 different neural networks and processes 120,000 tasks daily.

Work Experience

Data Engineer

2020 - 2022
Let's Enhance
  • Used a Triton Inference Server to significantly speed up neural processing, up to two times.
  • Maintained the production on Google Kubernetes Engine (GKE) and handled support requests and any detected errors.
  • Supported and improved CI/CD pipelines and made changes to suit them for ever-changing needs.
  • Developed custom client solutions, including image-CDN enhancement.
Technologies: Triton Compute, Python, TensorFlow, PyTorch, PostgreSQL, ClickHouse, Google Cloud, Google Kubernetes Engine (GKE), Kubernetes, Machine Learning, Git, Data Engineering, SQL, Data Architecture, Cloud Architecture, Business Intelligence (BI), Metabase, Amazon Web Services (AWS), Relational Databases, Helm, Terraform, GitLab CI/CD, CI/CD Pipelines, Business Intelligence (BI) Platforms, Data-driven Dashboards, Docker


2019 - 2021
Smart Home Solutions
  • Completed customers' orders to develop smart, custom-home appliances, custom PCBs, and software.
  • Completed a remotely controlled motor project and developed a Flutter app to control it.
  • Found and negotiated with customers interested in smart home solutions.
Technologies: Flutter, iOS, Android, KiCad, Autodesk Fusion 360, CNC Routers, PCB Design

Data Engineer

2018 - 2020
  • Created a model to remove the background from images. Wrote a RabbitMQ worker to process the images to make the model available for mobile apps.
  • Developed a financial-data webserver able to accept financial statements and perform queries upon them. Used Neo4j to store interconnections.
  • Created a facial-recognition system able to remember up to 150,000 unique people and classify them with a low-error rate. I used different types of workers, a few databases, and a few data sources.
  • Wrote a module for Android and iOS apps to have onboard-neural networks able to detect, crop, and encode faces to significantly speed up the back-end processing.
  • Developed load testing and profiling tools to identify issues and ensure consistency across different devices and services.
  • Deployed services using DigitalOcean and wrote custom deployment scripts.
  • Developed a custom dashboard to monitor ETL tasks and face recognition data processing.
  • Created a service to visualize the WHO Drug database to quickly find medical data by drugs and symptoms.
Technologies: Python, Deployment, Android, iOS, RabbitMQ, Redis, PostgreSQL, Machine Learning, Aiohttp, Data Engineering, SQL, Data Architecture, Data Visualization, Grafana, Data Warehousing, CouchDB, Relational Databases, Dimensional Modeling, MongoDB, NoSQL, Neo4j, React, JavaScript, Webhooks, Web Dashboards, Dashboards, React Native, Data Analytics, ETL, Data Validation, Data-driven Dashboards, Docker, Pandas, Data Pipelines

Machine Learning Engineer

2018 - 2018
  • Used Twitter API to crawl and collect all of the entity's mentions.
  • Classified texts and scored how customers are happy with the products they buy, using sentiment analysis models.
  • Used the Baas diffusion model to develop a model to score the products, according to their mentions in the social media, and predict sales.
Technologies: Python, Scikit-learn, Twitter API, Sentiment Analysis, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Data Visualization, NoSQL, MongoDB, Redis, Dimensional Modeling, Data Analysis, Azure, Data Validation, Pandas

Machine Learning Engineer

2016 - 2018
  • Developed the system to recognize web pages according to IAB's content taxonomy, using NLP techniques, including embedded learning, clustering, word2vec, and doc2vec.
  • Used and managed the in-house GPU cloud based on OpenStack.
  • Wrote an algorithm to compare facial expressions and developed the app with a distributed back end to read facial expressions on a scale.
  • Helped to organize the machine-learning weekend course.
  • Used the Julia language to write a high-speed implementation of the OPTICS data-mining algorithm to process a data lake.
Technologies: Python, TensorFlow, SpaCy, OpenStack, Data Analysis, Aiohttp, Julia, Data Lakes, MySQL, Pandas

Research Assistant

2016 - 2016
Institute of Mathematical Machines and Systems Problems NAS of Ukraine
  • Developed an aerial-imagery classification neural network for unmanned-aerial vehicles.
  • Searched patents to find the related algorithms and reproduced them to compare with our methods.
  • Created the images dataset to be used for neural-network training and validation.
Technologies: Python, MATLAB, Machine Learning, Patents, Linux, Ubuntu, Data Analysis

Let's Enhance Neural Engine
This is a software system to serve neural networks and process tasks.

The engine uses message queues, a multitude of workers, and inference servers to process tasks in the swiftest way. The system is deployed inside Kubernetes, well-monitored, and can automatically handle traffic spikes by scaling workers and servers.

I was the data engineer, and my responsibilities were to write parts of it, insert new models, and maintain them.

Face Recognition System

The face-recognition software system can handle massive inputs and process them in real-time. It utilizes RabbitMQ as a messaging queue and has multiple workers to do the processing, including GPU-encoding workers and memory-heavy matching workers.

The system can accept updates in real-time, utilizing pre-processing device modules to work more efficiently. The system is used for multiple purposes, including brick-and-mortar stores, marketing analysis, and social networks.

I designed the system and wrote most parts, including the workers, databases, and the pre-processing device modules.

UAV Systems Communication
I developed the UAV-components communication for Kray technologies's UAV with nine motors, computer vision, and self-driving capabilities. I set up the ROS to communicate between components and worked on positional-data streaming and consuming.

School Gamedev Projects

I developed a few games before entering university and started working commercially. Some of them received awards at local contests. I designed 2D and 3D games, employing: ray-tracing technology, a voxel engine, AI simulation, and the A* navigation. I presented some technologies at the national paper defense and earned two bronze medals.


Python, SQL, C++, C++98, Assembly, JavaScript, Julia, C++11


RabbitMQ, PyCharm, Vim Text Editor, Slack, Git, GitLab CI/CD, Google Kubernetes Engine (GKE), Autodesk Fusion 360, Grafana, MATLAB, KiCad, Helm, Terraform


Data Science, Business Intelligence (BI), ETL, Dimensional Modeling


Triton Compute, MacOS, Docker, Kubernetes, Linux, Ubuntu, OpenStack, Android, iOS, Amazon Web Services (AWS), Azure


Redis, PostgreSQL, Google Cloud, CouchDB, Relational Databases, MongoDB, NoSQL, Neo4j, Data Validation, Data Pipelines, ClickHouse, Data Lakes, MySQL


Software Engineering, Machine Learning, Computer Science, Data Engineering, Linear Algebra, Optimization, Deployment, Aiohttp, CNC Routers, TensorFlow Lite, Data Architecture, Cloud Architecture, Data Visualization, Data Warehousing, Data Analysis, Webhooks, Web Dashboards, Dashboards, Data Analytics, Streaming Data, Games, Game Engine Programming, CI/CD Pipelines, Business Intelligence (BI) Platforms, Data-driven Dashboards, Mathematical Analysis, Sentiment Analysis, Natural Language Processing (NLP), PCB Design, Metabase, Patents, Networking, Robot Operating System (ROS), GPS, Ray Tracing, 3D Games, GPT, Generative Pre-trained Transformers (GPT)


TensorFlow, SpaCy, PyTorch, Scikit-learn, OpenGL, Pandas, Twitter API, React, GLFW


Flutter, React Native

2015 - 2019

Bachelor's Degree in Software Engineering

National Technical University of Ukraine | Igor Sikorsky Kyiv Polytechnic Institute - Kyiv, Ukraine


Silver Medal


Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring