Bob Matcuk, Developer in Pittsburgh, PA, United States
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Bob Matcuk

Verified Expert  in Engineering

Full-stack Developer

Location
Pittsburgh, PA, United States
Toptal Member Since
March 26, 2018

Bob started writing code when he was eight as a hobby that grew into a career. He's built desktop apps for Windows, OS X, and Linux, mobile apps for iOS and Android, and web apps that receive upwards of 80,000 impressions per minute using a wide variety of the latest languages and technologies.

Portfolio

Rover.com
Vim Text Editor, HTML, Agile, GitHub, Web, CSS, Full-stack, Docker, MySQL...
Whitepages
Amazon Web Services (AWS), Vim Text Editor, HTML, Agile, RSpec, GitHub, SQL...
Contix
Vim Text Editor, HTML, MacOS, React Native, Agile, Windows, RSpec, GitHub, SQL...

Experience

Availability

Part-time

Preferred Environment

Git, Vim Text Editor, OS X

The most amazing...

...thing I've built was an artificial neural network utilizing bidirectional LSTM layers to classify user inputs into different search terms.

Work Experience

Software Engineer III

2018 - PRESENT
Rover.com
  • Built new features for Rover's Django-based web front-end.
  • Built unit tests for all new code. Rover has over 90% unit test coverage.
Technologies: Vim Text Editor, HTML, Agile, GitHub, Web, CSS, Full-stack, Docker, MySQL, Django, Python

Senior Software Engineer

2016 - 2018
Whitepages
  • Improved and maintained a core Ruby on Rails web app serving 80k+ page views per minute.
  • Migrated the system to a microservice architecture.
  • Migrated the system to Kubernetes on AWS and helped build tooling to automate deployments using Helm and Jenkins.
  • Improved performance decreasing total page load by more than 1.5 seconds.
  • Built a bi-directional LSTM neural network to classify visitor search terms.
Technologies: Amazon Web Services (AWS), Vim Text Editor, HTML, Agile, RSpec, GitHub, SQL, Web, JavaScript, CSS, Full-stack, PostgreSQL, Jenkins, Kubernetes, Docker, TensorFlow, Python, Ruby on Rails (RoR), Ruby

Senior Software Engineer

2013 - 2016
Contix
  • Built an NLP pipeline using RabbitMQ, Ruby, and Java to ingest tweets in real time, perform entity recognition, and perform machine learning techniques to classify the tweets.
  • Built a restful API and web app front-end using Ruby on Rails to display real-time news alerts using web sockets.
  • Built a native Windows application (in C#) and a native Mac OS X application (using Objective-C) that used the API and web socket connections to display news in real time.
  • Created a React app that was meant to replace both the web front-end and native apps (via Electron) reusing as much code as possible. The web front-end piece was completed, and the desktop piece was mostly done (I just needed to work in native notifications), but the company ran out of funding.
Technologies: Vim Text Editor, HTML, MacOS, React Native, Agile, Windows, RSpec, GitHub, SQL, jQuery, Web, JavaScript, CSS, Full-stack, MySQL, RabbitMQ, Node.js, Java, Objective-C, C#, React, Ruby on Rails (RoR), Ruby

Senior Software Engineer

2011 - 2013
OpenArc
  • Worked with clients to gather requirements, define features, develop, release, deploy, and maintain many software systems.
  • Built a custom land-survey plotting app using OpenLayers and PostGIS.
  • Integrated with many third-party APIs including Braintree for payments.
  • Contributed to open-source software such as OpenLayers.
Technologies: HTML, SQL, jQuery, Web, JavaScript, CSS, Full-stack, PostGIS, PostgreSQL, Git, C#, PHP, Ruby on Rails (RoR), Ruby

Senior Software Engineer

2009 - 2011
Four Rivers Software Systems
  • Developed a mobile-focused web app using VB.Net.
  • Worked with clients to gather requirements and develop customizations for their organization.
Technologies: Waterfall Development, HTML, Web, CSS, Full-stack, C++, ASP.NET, C#, VB.NET

Hireology

Hireology was a major client of mine while working at OpenArc. At the time, I was the sole developer, working directly with the client to implement new features, improve payment flows with the Braintree API, and fix bugs.

Web-starter-kit

https://github.com/bmatcuk/web-starter-kit
Web-starter-kit is a simple example project that can be used as a good starting point for building a React web app using Webpack, including support for hot reload. The starter kit can build isomorphic apps where static pages can be pre-rendered, and all pages can be rendered server-side for improved SEO.

Html-brunch-static

https://github.com/bmatcuk/html-brunch-static
Brunch is a build tool for JavaScript and CSS that focuses on simplicity. Html-brunch-static is a plugin that adds support for building static HTML as well with pluggable support for several alternative languages such as Pug/Jade, Markdown, and Handlebars.

Doublestar

https://github.com/bmatcuk/doublestar
Doublestar is a drop-in replacement for Golang's built-in path Match and Glob functions that adds support for doublestars, a.k.a. globstars. For example: path/**/match would recursively match any file or directory called "match" under the "path" directory.

Additional Code Samples on My Github

https://github.com/bmatcuk
I have many open source projects available on GitHub in a variety of languages.

Languages

Python, SQL, CSS, JavaScript, Ruby, HTML, C#, Objective-C, Java, PHP, VB.NET, C++

Frameworks

Ruby on Rails (RoR), Bootstrap, Django, Flask, minitest, React Native, ASP.NET

Libraries/APIs

Node.js, jQuery, React, TensorFlow

Tools

GitHub, RSpec, Git, Mocha, Webpack, Vim Text Editor, Jenkins, RabbitMQ

Paradigms

Test-driven Development (TDD), Waterfall Development, Agile

Platforms

Web, Windows, MacOS, Linux, OS X, Docker, Kubernetes, Amazon Web Services (AWS), iOS, Android

Storage

MySQL, PostgreSQL, Redis, PostGIS

Other

Full-stack

2001 - 2005

Bachelor's Degree in Electrical Engineering

Penn State University - State College, PA

2001 - 2005

Bachelor's Degree in Computer Science and Engineering

Penn State University - State College, PA

JANUARY 2019 - PRESENT

React Native Academy

Toptal

NOVEMBER 2018 - PRESENT

Blockchain Specialization

Coursera

AUGUST 2016 - PRESENT

Machine Learning

Stanford University | via Coursera

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