Experience

Modelbit

• United States
• Software Development
• 1 - 100 Employee

• Software Engineer

  • Feb 2022 - Present

  Modelbit is the fastest way for data scientists to deploy machine learning models. Modelbit is the fastest way for data scientists to deploy machine learning models.



Sisense

• United States
• Software Development
• 400 - 500 Employee

• Software Architect

  • May 2019 - Jan 2022



Periscope Data

• Technology, Information and Internet

• Software Engineer

  • Nov 2013 - May 2019

  If you give someone a static report, they'll want a second one tomorrow. If you give them a self-updating dashboard with live, dynamic filters, they'll be set all quarter. Here at Periscope we are building tools not just to let folks answer questions, but to build question answering robots of their own. You should come work with us! I work on many things here at Periscope, my passion generally being system design and building tools/frameworks to help others run faster. I'm a big champion of the Go language and we use it for most of our backend services. I've recently been slowly building out our small constellation of microservices as we try to keep complexity at a minimum whilst keep hundreds of thousands of charts up-to-date. Show less



Google

• United States
• Software Development
• 700 & Above Employee

• Software Engineer

  • Feb 2011 - Nov 2013



TokBox (now Vonage)

• United States
• Technology, Information and Internet
• 1 - 100 Employee

• Software Engineer

  • Aug 2007 - Feb 2011



University of Rochester

• Student

  • 2003 - 2007



NASA Ames Research Center

• United States
• Aviation and Aerospace Component Manufacturing
• 700 & Above Employee

• Intern

  • May 2006 - Aug 2006

  Worked in C++ to develop a program which normalized and plotted GPS coordinates in Google Earth KML, then used the path to determine the probable pose of the airplane, which was then used to orient and position aerial pictures taken from the plane into Google Earth. The results of my work can be seen by turning on the National Geographic MegaFlyover layer in Google Earth, and zooming into one of the plane icons on the terrain. Worked in C++ to develop a program which normalized and plotted GPS coordinates in Google Earth KML, then used the path to determine the probable pose of the airplane, which was then used to orient and position aerial pictures taken from the plane into Google Earth. The results of my work can be seen by turning on the National Geographic MegaFlyover layer in Google Earth, and zooming into one of the plane icons on the terrain.