Simon Szalai, Developer in Vancouver, BC, Canada
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Simon Szalai

Verified Expert  in Engineering

AI Specialist and Software Developer

Location
Vancouver, BC, Canada
Toptal Member Since
February 8, 2022

Simon is an accomplished software craftsman with over six years of experience in AI, data science, and application development. His mastery of Python and TypeScript, combined with his ability to quickly master new technologies, sets him apart. He is the co-founder and CTO of a vertical farming startup that raised over $400k so far. He secured third place at the Creative Destruction Labs Quantum Hackathon with the first-ever implementation of the Quantum Active Inference algorithm.

Portfolio

Raiz Vertical Farms
Python, Raspberry Pi, Electronic Sensors, Google Cloud, Deepnote...
Quantified Citizen
Python, Dagster, TypeScript, React, Flutter, Data Science, OpenAI GPT-3 API...
Bicameral NFT
PyTorch, TensorFlow, Deepnote, Python, Pandas, Matplotlib...

Experience

Availability

Full-time

Preferred Environment

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

The most amazing...

...project I completed is the Quantum Active Inference algorithm, steering an agent through environments extending into the Quantum Realm.

Work Experience

Co-founder | CTO

2020 - 2024
Raiz Vertical Farms
  • Built a first-principles-based simulation to model the behavior of the vertical farm under different weather conditions. This enables us to run experiments much faster and accurately predict OPEX before deployment.
  • Designed and implemented an environment control system from scratch.
  • Contributed to conceptualizing tokenized fractional farm financing.
Technologies: Python, Raspberry Pi, Electronic Sensors, Google Cloud, Deepnote, Process Simulation, Data Collection, Data Science, Predictive Modeling, Prompt Engineering, ChatGPT, Machine Learning

Senior Full-stack Developer

2022 - 2023
Quantified Citizen
  • Designed and built a real-time data processing pipeline using Python and Dagster.
  • Implemented a React app embedded in a Flutter web view to display study results generated by the data pipeline.
  • Cleaned, analyzed, and displayed data collected through the mobile platform.
Technologies: Python, Dagster, TypeScript, React, Flutter, Data Science, OpenAI GPT-3 API, OpenAI GPT-4 API, Prompt Engineering, ChatGPT, Machine Learning

AI Specialist

2021 - 2022
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.
  • Laid the foundations for the technology to be deployed as an API in the future.
Technologies: PyTorch, TensorFlow, Deepnote, Python, Pandas, Matplotlib, Artificial Intelligence (AI), Computer Vision, Machine Learning

Full-stack Engineer

2020 - 2022
KitchenMate
  • 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, Amazon Web Services (AWS), Python, PostgreSQL, JavaScript, Artificial Intelligence (AI), Machine Learning

Full-stack Engineer

2018 - 2020
SynerScope
  • 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, Node.js, Docker, PostgreSQL, Go, PyTorch, Artificial Intelligence (AI), Machine Learning

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, Computer Vision

Co-founder | CTO

2015 - 2017
Intersection Records
  • Set up an electronic record label, including website, distribution, and promotion.
  • Created artwork, released, and promoted over ten albums.
  • Helped organize live events with artists to promote the albums.
Technologies: WordPress, Photoshop CC

Quantum Active Inference

https://github.com/simonszalai/Creative-Destruction-Quantum-Hackathon-2022
I won third place in Creative Destruction Lab's Quantum Hackathon in 2022 with this project, which navigates an agent through environments extending into the Quantum Realm. This algorithm aims to demonstrate Quantum Advantage in multiplayer environments.

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.

Transform Data into Insights with Dagster and Deepnote Lecture

https://www.udemy.com/course/transform-data-into-insights-with-dagster-and-deepnote/
Created this 38-lecture course on Udemy with 8.5 hours of video materials. It teaches students how to use Dagster and Deepnote to extract valuable business insights from real-world data. It includes lessons on accessing, cleaning, transforming, and storing data.

SorterBot

https://github.com/simonszalai/sorterbot_cloud
This project controls a small robotic arm to automatically identify, classify and sort small objects with a magnet. It includes control software running on a Raspberry Pi, a control panel web app and a cloud service for inference using YOLO.

Languages

TypeScript, Python, JavaScript, Go, C++

Frameworks

React Native, Qt, Flutter, Django, Redux

Libraries/APIs

Node.js, React, PyTorch, Pandas, Matplotlib, TensorFlow, OpenCV

Paradigms

Data Science

Platforms

MacOS, Visual Studio Code (VS Code), Firebase, Linux, Amazon Web Services (AWS), Docker, Raspberry Pi, WordPress

Storage

PostgreSQL, Google Cloud

Other

Deepnote, Data Collection, Artificial Intelligence (AI), Computer Vision, Dagster, Data Engineering, OpenAI GPT-3 API, OpenAI GPT-4 API, Prompt Engineering, ChatGPT, Machine Learning, Electronic Sensors, Process Simulation, Deep Learning, Predictive Modeling, Object Detection, Business Administration, Reinforcement Learning, Deep Reinforcement Learning, Quantum Machine Learning, Quantum Computing, ISO Compliance, Robotics

Tools

You Only Look Once (YOLO), LabVIEW, Photoshop CC

2019 - 2020

Master's Degree in Business Administration (MBA)

Quantic School of Business and Technology - Online

2010 - 2014

Bachelor's Degree in Chemistry

University of Szeged - Szeged, Hungary

AUGUST 2021 - PRESENT

Qiskit Global Summer School on Quantum Machine Learning

IBM

MAY 2020 - PRESENT

Deep Reinforcement Learning Nanodegree

Udacity

OCTOBER 2018 - PRESENT

Deep Learning by Andrew Ng

Coursera

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