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Deep Knowledge in Machine Learning, AR/VR, GPU/CPU/DSP, High Performance
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Specialties: Deep learning, Machine learning, performance optimization, Computer graphics, parallel computing, graphics drivers, high performance computing, GPGPU computing
Washington State University
Doctor of Philosophy (Ph.D.), Engineering
N/A – Present
Chinese Academy of Sciences
Master
N/A – Present
University of Science and Technology Beijing
Bachelor's degree, Mechanical Engineering
N/A – Present
Apple
AR/VR Software Develop Engineer
November 1, 2022 – Present
California, United States · On-site
Intel Corporation
Deep Learning Software Engineer | Artificial Intelligence Analytics Group
July 1, 2017 – November 1, 2022
Santa Clara, California
Intel Corporation
Senior Applicaiton Software Engineer | Apple Enabling Team
April 1, 2016 – June 1, 2017
Santa Clara, California
AMD
Member of Technical Staff GPU Software Engineer
March 1, 2008 – April 1, 2016
sunnyvale, CA
Clearspeed Technology
Application Software Engineer
January 1, 2006 – February 1, 2008
San Francisco Bay Area
IBM
Software Engineer
January 1, 2005 – January 1, 2006
Poughkeepsie, New York, United States
Cultural Fit Analysis
The candidate has a long and diverse career history in hardware and software optimization, spanning GPUs, CPUs, and specialized co-processors, and more recently moving into AR/VR and ML. This breadth of experience suggests an ability to adapt to different technological landscapes and contribute to varied projects. The progression from hardware-centric roles to deep learning and AR/VR aligns well with the evolving demands of an ML Engineer role, indicating a continuous learning mindset. However, the lack of explicit project diversity beyond core engineering tasks makes it challenging to fully assess cultural fit in terms of innovation or cross-functional collaboration.
Soft Skills & Operational Fit
The candidate's extensive experience across multiple major technology companies (Apple, Intel, AMD, IBM) suggests strong adaptability, problem-solving skills, and the ability to work within complex engineering environments. The focus on optimization and performance indicates a detail-oriented and results-driven approach. However, without specific project details or interview data, it's difficult to assess collaboration or leadership styles.