Simon Szalai, AI Specialist and Software Developer in Toronto, ON, Canada
Simon Szalai

AI Specialist and Software Developer in Toronto, ON, Canada

Member since February 8, 2022
Simon is a software craftsman focusing on AI, Deep Learning, cloud computing, and consumer apps. He is proficient with Python and TypeScript and known for picking up new technologies as needed. He saved a client approximately 40 million EUR a year in collaboration with his team by increasing prediction accuracy and delivered a serverless React project to manage the day-to-day activities of a manufacturing company. Previous roles have included acting CTO and full-stack engineer.
Simon is now available for hire


  • Bicameral NFT
    PyTorch, TensorFlow, Google Colaboratory (Colab), Deepnote, Python, Pandas...
  • Raiz Vertical Farms
    Python, Raspberry Pi, Electronic Sensors, Google Cloud, Google BigQuery...
  • KitchenMate
    TypeScript, Node.js, React, AngularJS, Amazon Web Services (AWS), Heroku...



Toronto, ON, Canada



Preferred Environment

MacOS, Linux, Visual Studio Code, TypeScript, Python, PyTorch, TensorFlow, Deepnote, Amazon Web Services (AWS), Google Cloud

The most amazing...

...tool I've developed is a machine learning pipeline that turns brainwave data and digital artwork into a unique, animated art piece.


  • AI Specialist

    2021 - PRESENT
    Bicameral NFT
    • Developed a machine learning pipeline to turn brainwave data and digital artwork into a unique animated art piece, using Generative Adversarial Networks (GANs).
    • Recruited a team to use this technology to create an NFT collection of 5,000 pieces on the Ethereum blockchain.
    • Lay the foundations for the technology to be deployed as an API in the future.
    Technologies: PyTorch, TensorFlow, Google Colaboratory (Colab), Deepnote, Python, Pandas, Matplotlib, Artificial Intelligence (AI), Computer Vision
  • Acting CTO

    2020 - PRESENT
    Raiz Vertical Farms
    • Developed a simulation from first principles to help design an energy-efficient greenhouse.
    • Ran a successful crowdfunding campaign with my team, raising $30,000.
    • Participated in defining strategy and product development direction.
    Technologies: Python, Raspberry Pi, Electronic Sensors, Google Cloud, Google BigQuery, Deepnote, Process Simulation, Data Collection
  • Full-stack Engineer

    2020 - PRESENT
    • Designed and implemented control software running on an Android tablet for the hot food kiosk using Ionic React and Node.js.
    • Evolved requirements constantly despite a lot of ambiguity.
    • Oversaw the software integration of many different hardware. systems (AI vision system, induction cookers, cameras, payment terminals, smart fridge, WiFi hotspot, etc.).
    • Expanded a user-facing mobile app and internal tools using JavaScript.
    Technologies: TypeScript, Node.js, React, AngularJS, Amazon Web Services (AWS), Heroku, Ionic, AutoML, Python, PostgreSQL, JavaScript, Artificial Intelligence (AI)
  • Full-stack Engineer

    2018 - 2020
    • Executed the transition of SynerScope's entire data management platform from an on-premises app to a microservices-based cloud-native solution on Azure.
    • Increased the prediction accuracy of a client's required tools and expertise for field-work of their employees from 80% to 99.98% on two million visits, saving approximately 40 million EUR a year in collaboration with my team.
    • Engineered data pipelines to move documents, metadata, text, and images between Hadoop, Azure, and various databases.
    • Deployed an image vectorizer model to Azure Cloud as a REST API using Docker.
    Technologies: JavaScript, Python, Vue, Meteor, Node.js, Azure, C#, .NET, Docker, Docker Compose, Hadoop, MySQL, NoSQL, PostgreSQL, Go, PyTorch, Databricks, Spark, Artificial Intelligence (AI)
  • Software Engineer

    2018 - 2018
    Dekimo Experts
    • Developed a computer vision product to classify cells in microscope images.
    • Delivered core development in C++, UI in QML using Qt5, image manipulation in OpenCV.
    • Contributed to the project while learning C++ autonomously from zero.
    Technologies: C++, Qt, QML, Computer Vision


  • Quantum Active Inference

    Currently building a quantum version of the active inference algorithm, which is a plausible algorithm that might be close to how "the brain works." The project's goal is to set it up in a competitive environment, where it can be compared to its classical counterpart.

  • Custom CRM and ISO Compliance Software

    A serverless React project running on Firebase to manage day-to-day activities in a small manufacturing company. It includes business document creation (offers, order confirmations, shipping notes, and invoices), automatically sending invoices to the tax authority, and processing client and inventory management.

  • SorterBot

    A Cloud application to control a swarm of Raspberry Pis, featuring a real-time dashboard, a deep learning inference engine, 1-click Cloud deployment, and dataset labeling tools. SorterBot is able to control an arbitrary number of Raspberry Pis, each connected to a robotic arm equipped with a camera and an electromagnet. When a session is started, the arm scans the area in front of it, locates the objects and containers within its reach, then automatically divides the objects into as many groups as many containers were found. Finally, it moves the objects to their corresponding containers.


  • Languages

    Python, JavaScript, TypeScript, C#, Go, C++, QML, Bash
  • Libraries/APIs

    Node.js, React, PyTorch, Pandas, TensorFlow, Matplotlib, Vue, OpenCV
  • Platforms

    Visual Studio Code, MacOS, Linux, Amazon Web Services (AWS), Heroku, Meteor, Azure, Docker, Databricks, Raspberry Pi, Firebase, Amazon EC2
  • Other

    Deepnote, Deep Learning, Artificial Intelligence (AI), Computer Vision, Machine Learning, Business Administration, Google Colaboratory (Colab), Electronic Sensors, Google BigQuery, Process Simulation, Data Collection, Reinforcement Learning, Deep Reinforcement Learning, Linear Algebra, Quantum Machine Learning, Quantum Computing, Pennylane, Firebase Cloud Functions, Robotics, GitHub Actions, AWS Cloud Development, Object Detection, Classification, Classification Algorithms
  • Frameworks

    AngularJS, Ionic, .NET, Hadoop, Spark, Qt, Django, React Native
  • Tools

    LabVIEW, AutoML, Docker Compose, Amazon ECS (Amazon Elastic Container Service)
  • Storage

    Google Cloud, PostgreSQL, MySQL, NoSQL, Amazon S3 (AWS S3)


  • Master's Degree in Business Administration (MBA)
    2019 - 2020
    Quantic School of Business and Technology - Online
  • Bachelor's Degree in Chemistry
    2010 - 2014
    University of Szeged - Szeged, Hungary


  • Deep Reinforcement Learning Nanodegree
    MAY 2020 - PRESENT
  • Deep Learning by Andrew Ng

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