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/dgarwin | github.com/dgarwin | (718) 541-0186
PROFESSIONAL EXPERIENCE
Autonomous Healthcare
Research Engineer Oct 2019 - Present
Implemented infrastructure in Python, conducted literature reviews, and executed Machine Learning experiments analysis for neonatal pain classification.
Lifion
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.
EDUCATION
NYU Poly May 2016
BS in Computer Science, Applied Physics