Cody Hsieh
ML EngineerAI for Regulatory Headaches, Ex-Amazon, UC Berkeley '19
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI for Regulatory Headaches, Ex-Amazon, UC Berkeley '19
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of California, Berkeley EECS grad interested in the future applications of machine learning. Currently creating and designing ML data processing components/pipelines for Amazon Advertising. Previously explored distributed reinforcement learning as an Artificial Intelligence Intern at Intel AI and using convolutional neural nets for estimating HRTF (head-related transfer functions) for spatial audio.
University of California, Berkeley
Bachelor of Science (B.S.), Electrical Engineering and Computer Science
January 1, 2015 – January 1, 2019
Mount Mercy University
Discrete Mathematics
January 1, 2014 – January 1, 2014
Linn Mar High School
High School
January 1, 2011 – January 1, 2015
BrainPOP
AI Engineer
July 1, 2023 – December 1, 2023
New York City Metropolitan Area
Amazon
Software Engineer
July 1, 2019 – July 1, 2022
New York, New York, United States
Intel Corporation
Artificial Intelligence Intern
June 1, 2018 – December 1, 2018
Mobile Developers of Berkeley
Machine Learning App Lead
January 1, 2018 – December 1, 2018
Adobe
Software Engineering Intern
May 1, 2017 – August 1, 2017
Mobile Developers of Berkeley
UI/UX Consultant/Android Platform Lead
August 1, 2016 – May 1, 2017
Rockwell Collins
Undergraduate Engineering Intern
May 1, 2016 – August 1, 2016
Mobile Developers of Berkeley
Senior Developer
September 1, 2015 – May 1, 2016
Wirefly
November 1, 2016 – Present
• Web app in Flask enabling users to transfer money internationally cheaper than market value using a P2P network that minimizes international transactions • Built a simulator using Capital-One’s API and handled HTTP requests in Python to generate accounts looking to transfer currency and to actually run all the transfers
Qlic
January 1, 2016 – May 1, 2016
• Developed an Android app that communicates with nearby devices to share contact information (Facebook, Instagram, email, etc.) with multiple users instantly • Used Google’s Nearby API to send and parse contact information
Concentraid
August 1, 2015 – December 1, 2015
-Concentraid is a productivity app that uses proven methods to maximize efficiency and focus. -This Android app can provide users with easy timers that will provide users with short, high-intensity work periods with enough breaks to prevent the mind from being over-stressed.
Cultural Fit Analysis
The candidate has a diverse background spanning personal projects, academic research, and industry roles at large tech companies (Amazon, Intel, Adobe) and startups (BrainPOP). This breadth suggests adaptability to different organizational cultures. The target role is ML Engineer, which aligns well with the candidate's recent experience at BrainPOP and Amazon, as well as the Intel internship. The involvement in Mobile Developers of Berkeley, including leadership roles and teaching, indicates a collaborative and knowledge-sharing mindset. The personal projects demonstrate initiative and a passion for technology beyond formal employment.
Soft Skills & Operational Fit
The candidate's project descriptions and work experience indicate a proactive approach to problem-solving and a capacity for leading technical initiatives (e.g., Machine Learning App Lead, Android Platform Lead). The diverse project portfolio suggests adaptability and a willingness to explore different technologies and domains. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.