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AI PhD student at UT Austin | Research Engineer
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Master's in EECS specializing in AI and intelligent systems at Berkeley. Completed undergraduate at Berkeley studying Applied Math, Computer Science, and Data Science.
The University of Texas at Austin
Doctor of Philosophy - PhD, Artificial Intelligence
January 1, 2023 – January 1, 2027
University of California, Berkeley
Master's degree, Electrical Engineering and Computer Science
January 1, 2020 – January 1, 2021
East Brunswick High School
High School
January 1, 2013 – January 1, 2016
Microsoft
Research Intern
June 1, 2024 – August 1, 2024
Perplexity AI
Research Engineer
February 1, 2023 – December 1, 2023
Scale AI
Research Engineer
June 1, 2021 – December 1, 2022
Latent AI, Inc.
Research Intern
May 1, 2019 – August 1, 2019
Berkeley Artificial Intelligence Research
Researcher
September 1, 2018 – December 1, 2021
Machine Learning at Berkeley
Project Manager / Researcher
September 1, 2018 – May 1, 2021
SRI International
Computer Vision Intern
May 1, 2018 – December 1, 2018
Uizard Technologies
Machine Learning Engineer
February 1, 2018 – July 1, 2018
UC Berkeley College of Engineering
Teaching Assistant for Principles and Techniques of Data Science (DS100)
January 1, 2018 – May 1, 2018
SETI Institute
Machine Learning Researcher
September 1, 2017 – February 1, 2018
Berkeley, CA
Berkeley RISE Lab
Assistant Devops Engineer & Researcher
October 1, 2016 – June 1, 2018
Commvault
Software Engineering Intern
June 1, 2016 – August 1, 2016
Monmouth University
Summer Researcher
May 1, 2015 – August 1, 2015
New York Math Circle
Student
June 1, 2014 – August 1, 2014
Albumify
June 1, 2017 – Present
Top 10 at Mhacks hackathon - Webapp that combines popular album art with profile pictures using style transfer algorithm, written in Python with Keras and deployed on Google App Engine
Cultural Fit Analysis
The candidate's background is heavily skewed towards academic research and AI/ML, which might not directly align with a typical Backend Engineer role's day-to-day responsibilities. While the candidate has experience with backend technologies (Python, Java, Google App Engine), the primary focus has been on AI model development and optimization rather than scalable system architecture, API design, or database management. The project 'Albumify' shows some backend development, but it's a personal project. The breadth of skills is strong in AI/ML, but less so in core backend engineering principles for large-scale systems. This suggests a potential mismatch with a standard Backend Engineer role, though the candidate's intelligence and learning ability are high.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong problem-solving, analytical thinking, and independent work capabilities. Experience as a Project Manager and Teaching Assistant indicates leadership and communication skills. However, the resume primarily highlights research and academic roles, which may require further assessment for direct operational fit in a pure backend engineering role focused on product development and system reliability.