
Principal Machine Learning Engineer at Gaggle
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer specializing in the design and creation of resilient distributed systems utilizing Machine Learning, Natural Language Processing, and Recommender Systems.
Georgia Institute of Technology
Master of Science - MS, Analytics
January 1, 2019 – January 1, 2022
University of North Florida
Bachelor of Science, Computer & Information Science
January 1, 2007 – January 1, 2010
University of North Florida
Bachelor of Arts, History
January 1, 1999 – January 1, 2003
Gaggle
Principal Machine Learning Engineer
October 1, 2023 – Present
Gaggle
Senior Machine Learning Engineer
October 1, 2021 – October 1, 2023
Gaggle
Machine Learning Engineer
February 1, 2018 – October 1, 2021
IJHANA
Machine Learning Engineer / Software Engineer (Contractor)
April 1, 2017 – February 1, 2018
Metro Jacksonville
intoGo
Data Scientist / Machine Learning Engineer
March 1, 2016 – April 1, 2017
Metro Jacksonville
Gaggle
Senior Software Engineer - Machine Learning
January 1, 2016 – March 1, 2016
Remote
SportsYapper
Data Scientist
May 1, 2014 – January 1, 2016
Jacksonville, Florida
Ignite by Adecco
Senior Software Engineer / Data Engineer
June 1, 2013 – May 1, 2014
Jacksonville, Florida Area
Eventhash
Co-Founder/Machine Learning Engineer
January 1, 2013 – January 1, 2014
Jacksonville, Florida
Path.To
Software Engineer III
September 1, 2011 – June 1, 2013
Jacksonville, Florida
EverBank
Software Engineer II
December 1, 2010 – September 1, 2011
Metro Jacksonville
Cliqset
Software Engineer
June 1, 2009 – December 1, 2010
Metro Jacksonville
Cultural Fit Analysis
The candidate has a long and consistent career path focused on Machine Learning and Data Science, with multiple stints at startups and a return to Gaggle, indicating a preference for dynamic environments and a commitment to the field. Their diverse project experience, including recommendation systems, NLP, and real-time analytics, aligns well with innovative and data-driven cultures. The progression through various ML roles suggests adaptability and a continuous learning mindset. However, the lack of explicit project details or team collaboration descriptions limits a deeper cultural fit assessment.
Soft Skills & Operational Fit
The candidate's resume descriptions indicate a proactive approach to problem-solving and a clear understanding of project goals, as evidenced by their detailed explanations of system designs and reasons for leaving previous roles. Their experience as a Co-Founder also suggests entrepreneurial drive and leadership potential. However, without specific psychometric test results or interview data, a comprehensive assessment of soft skills and operational fit is limited.