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Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Natural Language Understanding, Autoregressive language generation, Multi-task learning, Graph Neural Networks, Knowledge Distillation, Information Retrieval and Learning-to-rank
UCLA
Master's degree, Computer Science
January 1, 2016 – January 1, 2017
UCLA
Doctor of Philosophy (PhD), Pharmacology
January 1, 2014 – January 1, 2018
Duke University
Non-degree Program
January 1, 2010 – January 1, 2014
Peking University
Bachelor of Science (B.Sc.), Science
January 1, 2006 – January 1, 2010
Meta
Machine Learning Engineer, Monetization GenAI
July 1, 2025 – Present
Menlo Park, California, United States · On-site
Software Engineer, Machine Learning
March 1, 2024 – July 1, 2025
Menlo Park, California, United States · On-site
Nextdoor
Lead, Notification ML
June 1, 2022 – March 1, 2024
Staff Software Engineer, Machine Learning
March 1, 2022 – June 1, 2022
Senior Software Engineer, Machine Learning
October 1, 2019 – March 1, 2022
Software Engineer, Machine Learning
March 1, 2018 – October 1, 2019
Scalable Analytics Institute
Machine Learning Research Assistant
June 1, 2017 – December 1, 2017
Greater Los Angeles Area
UCLA
Research Scientist
February 1, 2014 – June 1, 2016
Greater Los Angeles Area
Full Stack Python and Django Web Development Bootcamp
Udemy
June 24, 2026 – Present
Introduction to Linux
edX
June 24, 2026 – Present
Algorithms: Design and Analysis, Part 1
Coursera
June 24, 2026 – Present
edX Honor Code Certificate for Introduction to Computer Science and Programming Using Python
edX
June 24, 2026 – Present
edX Verified Certificate for Introduction to Computational Thinking and Data Science
edX
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in large, product-driven tech companies, which suggests an ability to thrive in fast-paced, collaborative environments. Their experience spans various ML applications (monetization, user engagement, notifications, knowledge graphs), indicating adaptability and a broad interest in applying ML to diverse problems. The progression through roles at LinkedIn and leadership at Nextdoor, Meta, and Instagram aligns with a growth-oriented culture. The academic background (PhD, Master's in CS) combined with industry experience shows a blend of theoretical rigor and practical application, which is often valued in ML roles. The lack of explicit project diversity outside of large tech companies might suggest a specific cultural alignment, but within that domain, the fit appears strong.
Soft Skills & Operational Fit
The candidate's experience as a 'Lead, Notification ML' at Nextdoor and 'Tech lead' at LinkedIn demonstrates strong leadership, team management, and mentorship abilities. Their collaboration with cross-functional teams and alignment with stakeholders indicate good operational fit and communication skills within a team context. The descriptions suggest a results-oriented approach, focusing on measurable business outcomes.