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Sr. Machine Learning Engineer @ Pinterest | Ex-Linkedin
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Physics Ph.D + CS Masters, 10 pending US patents Skilled in Python, machine learning, deep learning. Experienced in Tensorflow, Keras, Pytorch and Scikit-learn. Proficiency in neural network (Attention, Seq2seq, LSTM, RNN, GRU, CNN, Reinforcement Learning, GANs), Automatic Speech Recognition(ASR), image processing.
University of California, Riverside
Master's degree, Computer Science
January 1, 2016 – January 1, 2017
University of California, Riverside
Doctor of Philosophy (Ph.D.), Physics
January 1, 2011 – January 1, 2017
University of Science and Technology of China
Bachelor of Science (BS), Optics/Optical Sciences
January 1, 2007 – January 1, 2011
Sr. Machine Learning Engineer
May 1, 2024 – Present
Sr. Machine Learning Engineer
March 1, 2022 – May 1, 2024
Sunnyvale, California, United States
Machine Learning Engineer
May 1, 2020 – March 1, 2022
Sunnyvale, California, United States
Motorola Mobility (a Lenovo Company)
Staff Researcher, Deep Learning
March 1, 2019 – May 1, 2020
Motorola Mobility (a Lenovo Company)
Sr. Engineer, Machine Learning & Artificial Intelligence
September 1, 2017 – March 1, 2019
Structuring Machine Learning Projects (deeplearning.ai 3)
Coursera
June 24, 2026 – Present
Sequence Models (deeplearning.ai 5)
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning(deeplearning.ai 1)
Coursera
June 24, 2026 – Present
Automata
Coursera
June 24, 2026 – Present
An Introduction to Interactive Programming in Python
Coursera
June 24, 2026 – Present
Computing for Data Analysis
Coursera
June 24, 2026 – Present
Unconscious Bias
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Convolutional Neural Networks (deeplearning.ai 4)
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (deeplearning.ai 2)
Coursera
June 24, 2026 – Present
SAS Certified Base Programmer for SAS 9
SAS
June 24, 2026 – Present
Algorithms: Design and Analysis, Part 1
Coursera
June 24, 2026 – Present
Principles of Microeconomics
Coursera
June 24, 2026 – Present
edX Honor Code Certificate for Introduction to Big Data with Apache Spark
edX
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked at prominent tech companies (Pinterest, LinkedIn, Motorola Mobility) known for fast-paced, innovative environments. Their background in research and leading new initiatives (e.g., first in-house deep learning HDR solutions, first ASR system) suggests an innovative and proactive mindset. The target role is Backend Engineer, while the candidate's experience is heavily skewed towards Machine Learning Engineering. This represents a potential mismatch in core responsibilities, though ML Engineers often possess strong backend skills. The breadth of skills is focused on ML/AI, with less explicit mention of traditional backend engineering skills (e.g., distributed systems, API design, database management outside of ML contexts).
Soft Skills & Operational Fit
The candidate's experience as a tech lead and in driving cross-organizational initiatives suggests strong leadership, project management, and collaboration skills. Their work on engineering productivity initiatives indicates a focus on operational efficiency. However, specific details on communication style, stress handling, and team collaboration are not explicitly provided in the resume descriptions.