David Garwin
Research Engineer + Software Engineer

Trained and led teams of developers, designed enterprise solutions, and wrote plenty of code. After leading a company bringing coding to the juvenile detention world and leaving my day job, I now seek out software contracts that have direct social good impact

David Garwin
davidgarwin@gmail.com | linkedin.com/in/dgarwingithub.com/dgarwin | (718) 541-0186


Autonomous Healthcare    

Research Engineer                                 Oct 2019 - Present

  • Implemented infrastructure in Python, conducted literature reviews, and executed Machine Learning experiments analysis for neonatal pain classification.


Software Engineer                                Dec 2018 - Aug 2019

  • Designed, implemented, and deployed backend node.js solutions for the Lifion platform used by hundreds of concurrent users.

  • Introduced best practices for code documentation, solution research, and developer onboarding, leveraging both Jira and Confluence.

  • Researched and resolved dozens of bugs and support issues in multiple areas including:   node.js microservices and packages, the CI/CD pipeline, SQL and NoSQL data errors.

NYU (Operations Technology and Support Services)

Systems Architect                                  Jan 2018 - Dec 2018

Software Engineer                                Mar 2015 - Jan 2018

Programmer Analyst                                June 2015 - Mar 2015

  • Led development and architecture of 2 consecutive web apps, each with 3-8 developers.

  • Implemented, with one other developer, a RESTful API on top of an existing Oracle database, used by a new iOS app used by up to 500 simultaneous users.

  • Implemented a nightly data import procedure for a data aggregation web application used by NYU Public Safety, storing, connecting, and validating millions of student records across 16 different tables using C# and Microsoft SQL Server.

AreteX Systems    

Software Engineer                                 May 2016 - Jan  2017

  • Architected and led an interdisciplinary development team to create a machine-learning powered, real time, fault tolerant, medical device.

  • Implemented a RESTful API integrating: machine learning (logic), sensor reading, and hardware control modules. 

Machine Learning Engineer                             Nov 2013 - Nov 2014

  • Created a machine learning data pipeline in Matlab and conducted machine learning models and feature research for predicting sedation levels in ICU patients.


NYU Poly                                                                 May  2016
BS in Computer Science, Applied Physics