Edward is a Senior Python Developer with 6 years of experience creating back-end services using Flask, Django, SQL, MongoDB, Redis, AWS, and Circle CI. He is an AWS Certified Developer with several prestigious technology awards and additional skills in C++, JavaScript, Docker, Kubernetes, Git, GitHub, OOP, and Design Patterns. Edward is also keenly interested in AI, space, and gene editing and works with clients and distributed teams in a fully remote capacity.
Developed and maintained the app's back end, allowing users to watch and manage retail inventories.
Created three integrations with third-party back-end services to ingest automatically, process automatically, and store necessary data daily and implemented redundancy to cope with regularly failing third-party services.
Implemented performant SQL queries to analyze and process 5 million rows with complex joins, returning summarized results to user queries in real time.
Migrated a large portion of the project from Python 2 to Python 3.
Fixed unit and functional tests caused by Python 2 to Python 3 migration.
Handled most of the CI/CD (Circle CI) changes required when transitioning from Python 2 to Python 3, ensuring it worked well with the existing CI/CD systems.
Developed and maintained the app's back end that allowed users to search, track, and log hundreds of multiphase experiments with dynamically changing specifications.
Connected the app to Slack and Asana by using their APIs, created bots to notify app users about their tasks and overall progress, and synchronized the data between the database, Slack, and Asana.
Developed the CI/CD that ran tests and database migrations and deployed the back end to AWS Lambda.
Designed and developed the "dataset format for AI" and played a key role in getting the project from 0 to 2,400 stars (github.com/activeloopai/hub).
Co-developed the app back end that visualizes AI datasets and allows users to zoom in/out, batch, and more.
Developed a pipeline for ingesting datasets, training models, and running inference in a multimachine, parallelized environment using Kubernetes-like technology.
Developed a C++ back end, co-developed a Python back end, and took part in all stages of project development.
Designed and developed a custom, real-time database for aerial heatmaps with zoom-in-and-out support (the database and its Python back end allowed users to view 80GB of data in real time despite strict I/O limitations).
Modified an open-source DSD project, created a cross-language interoperability layer between LabVIEW and C++, allowing LabVIEW developers to access the DSD functionality (the original project is available on github.com/szechyjs/dsd).
A university project with the goal to parse photos of Sudoku into their digital form. Used OpenCV and open-source algorithms to crop the Sudoku grid from the background. Next, used breadth-first search (flood fill) to separate each digit from the grid into separate images. The optical character reader labeled each digit image. Used the handwritten MNIST dataset and a known convolution network to train the model to develop the OCR. After that, fine-tuned it with programmatically generated (Pillow) printed digits with a dozen fonts. Resulting OCR had a 99% accuracy, which translated into 90% accuracy for the entire Sudoku grid.
A research project to detect a drone or plane's location by tracking changes in surface images beneath the drone. This was a backup in case GPS navigation failed for any reason. Using linear algebra and OpenCV algorithms, the position detection algorithm got good results. While it could not detect the drone's precise position, it was enough to direct it to the desired place. The performance of the analysis was also acceptable enough to run on an onboard Raspberry Pi.
The client, a signal processing company, needed a LabVIEW API allowing them to listen to and transmit a wide range of radio frequencies using HackRF devices. Developed a cross-language interoperability layer between LabVIEW and HackRF C++ drivers, allowing LabVIEW developers to build seamless and low-latency communication with HackRF devices.
Developed a full-stack demo application for a 2-founder AI startup to pitch their idea. Designed the website using Material UI and developed the front end, enabling users to search with various filtering capabilities. Developed an Elasticsearch-backed Python back end to handle incoming front-end requests.
Started learning to program at the age of 12. After rigorous and persistent training, became exceptionally skilled at algorithms and data structures and won the silver medal at IOI 2014, Taiwan.
Education
AWS Certified Developer - Associate (Expires Oct 2026)
Amazon Web Services (AWS)
2023 - 2023
Bachelor's Degree, Applied Mathematics and Computer Science
