Imre Kiss
Backend EngineerDirector, Applied Science at Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Director, Applied Science at Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Dr. Imre Kiss is a Director of Applied Science at Amazon, where he leads cutting-edge research and development in Artificial Intelligence (AI) and Machine Learning (ML), Imre plays a pivotal role in Amazon's Artificial General Intelligence (AGI) initiatives, most notably in the development of Amazon Nova family of multimodal foundation models—including Micro, Lite, Pro, Canvas, and Reel—launched in late 2024. Previously, Imre led a range of initiatives in Natural Language Understanding and Entity Resolution at Amazon Alexa, serving customers on hundreds of millions of Alexa devices.
Tampere University of Technology 1965-2018
PhD, Information Technology
January 1, 1996 – January 1, 2001
Budapest University of Technology and Economics
MSc, Electrical Engineering, Telecommunications
January 1, 1992 – January 1, 1996
Amazon
Director, Applied Science
October 1, 2022 – Present
Amazon
Senior Manager, Machine Learning
October 1, 2017 – October 1, 2022
Amazon
Machine Learning Manager
May 1, 2015 – October 1, 2022
Amazon
Senior Machine Learning Scientist
June 1, 2012 – April 1, 2015
Vlingo
Senior Speech Scientist
January 1, 2012 – May 1, 2012
Cambridge, MA
Nokia Research Center Cambridge
Principal Member of Research Staff
December 1, 2007 – January 1, 2012
Nokia Research Center
Principal Scientist
January 1, 2007 – December 1, 2007
Nokia Research Center
Research Manager
January 1, 2004 – December 1, 2006
Nokia Research Center
Senior Research Engineer
May 1, 2001 – December 1, 2003
Nokia Research Center
Research Engineer
July 1, 1996 – April 1, 2001
Cultural Fit Analysis
The candidate has a strong background in research and applied science within large corporate environments (Amazon, Nokia). While this demonstrates adaptability to structured organizations, the target role of 'Backend Engineer' might require a different cultural fit focusing on core software development practices rather than research and management. The candidate's experience is heavily skewed towards ML/NLP, which may not directly align with typical backend engineering roles unless the role has a strong ML infrastructure component. The lack of diverse project experience outside of ML/NLP research and management could indicate a narrower focus.
Soft Skills & Operational Fit
The candidate's career progression into management roles at Amazon suggests strong leadership, team management, and strategic thinking. The description for the Machine Learning Manager role indicates experience in hiring and team building. However, specific details on collaboration style, stress handling, or direct operational fit for a 'Backend Engineer' role are not explicitly provided in the given data.