MATTHEW PECKO

Software Engineer

Relevant Experience

Freelance

Full stack Engineer(2022 - Present)

  • Developing websites for clients in WordPress, using HTML, CSS, and JavaScript.
  • Customizing front end Javascript frameworks like bootstrap for customerrequirements.
  • Setting up development environments for efficient and fluid development lifecycle.
  • Migrating code from development machine to web server using Git and sftp.

Rockland Career Center

Full stack Engineer intern (2018 - 2019)

  • Converted a legacy paper-and-pencil system into an automated website and app.
  • Developed a mobile app in React Native to streamline the user experience.
  • Built an API in node to interact with the Wordpress backend from the mobile app.
  • Created a Wordpress plugin to save custom information like resumes' in the SQL database.
  • Designed an extensive UI/UX for desktop and mobile, to match job seekers and employers.
  • Trained a team of career specialists to use administrative features on the website.

Rockland Small Business Development Center

Full stack Engineer intern (2016 - 2017)

  • Developed the SBDC website using Wordpress.
  • Created mobile apps in React Native for SBDC clients.
  • Built e-commerce websites using Shopify for SBDC clients.
  • Developed Python and C++ scripts to convert legacy product data into a format used by Shopify.

Projects & Hackathons

ML Music Generator

View on Github →

  • Trained a Pytorch Transformer with ~150k songs to generate music.
  • Lead and mentored 4 students in training the Deep Learning model.
  • Developed a Flask API to inference the model and return a JSON object to the client.
  • Created Wordpress middleware to serve a front-end website to call the backend API.
  • Rendered the generated music with a Typescript library called Open Sheet Music Display.
  • Awarded “Best Project” and was presented for CCNY’s “Industry Day 2022”.

GOES-R Hackathon submission 2021

View on Github →

  • Awarded first place in the “Computer Science” category.
  • Constructed a dataset of satellite images to be used in ML frameworks using Python.
  • Worked in a team of three in a 48 hour coding challenge window.

Selfie Recognition Lookup System

View on Github →

  • Developed an application to match uploaded user selfies to similar faces.
  • Used a trained PyTorch model, Facenet, to support facial-recognition.
  • Connected the model to a SQL database that stored selfies, and other user data.