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Applied DL Research Scientist. GenAI. Efficient RL @ NVIDIA
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Universidad de Zaragoza
Doctor of Philosophy (PhD), Engineering Systems and Computing
January 1, 2009 – January 1, 2013
Universidad de Zaragoza
Master's Degree, Systems Engineering and Computing
January 1, 2008 – January 1, 2009
Universidad de Zaragoza
Computer Engineering
January 1, 2001 – January 1, 2007
NVIDIA
Applied DL Research Scientist
April 1, 2021 – Present
Cerebras Systems
MTS
May 1, 2019 – April 1, 2021
NVIDIA
Senior Deep Learning Architect
December 1, 2016 – May 1, 2019
San Francisco Bay Area
University of Toronto
Postdoctoral Research Fellow
July 1, 2013 – October 1, 2016
Greater Toronto Area, Canada
University of Rochester
Visiting scholar
August 1, 2012 – December 1, 2012
Rochester, New York Metropolitan Area
STMicroelectronics
Interim Engineering Intern
September 1, 2011 – December 1, 2011
Greater Grenoble Metropolitan Area
STMicroelectronics
Interim Engineering Intern
September 1, 2010 – December 1, 2010
Greater Grenoble Metropolitan Area
Universitat Politècnica de Catalunya
Visiting Scholar
August 1, 2008 – February 1, 2009
Greater Barcelona Metropolitan Area
Universidad de Zaragoza
PHD Student
January 1, 2008 – May 1, 2013
Zaragoza, Aragon, Spain
Cultural Fit Analysis
The candidate's background is heavily skewed towards deep learning research, hardware architecture, and academic roles. While these skills are highly specialized and valuable, the direct alignment with a general 'Backend Engineer' role, which typically involves broader software development, API design, database management, and distributed systems, is not immediately apparent. The focus on cutting-edge AI hardware suggests a preference for research and specialized optimization rather than general-purpose backend development. This might indicate a potential mismatch if the target role is not heavily focused on AI infrastructure or performance optimization.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in architectural design and research, suggesting strong problem-solving, innovation, and independent work capabilities. However, direct evidence of communication, teamwork, or project management in a typical backend engineering team context is not explicitly detailed in the provided descriptions.