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Engineering Manager, AI Platform at Netflix
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Carnegie Mellon University
Master of Information Systems
January 1, 2015 – January 1, 2016
Zhejiang University
Bachelor of Science, Software Engineering
January 1, 2010 – January 1, 2015
Netflix
Engineering Manager, AI Platform
April 1, 2026 – Present
Amazon Web Services (AWS)
Software Development Manager, AWS SageMaker
April 1, 2023 – Present
Amazon Web Services (AWS)
Senior Software Engineer, AWS SageMaker
April 1, 2022 – March 1, 2023
Amazon Web Services (AWS)
Software Engineer, AWS SageMaker
March 1, 2017 – March 1, 2022
Amazon Web Services
Software Engineer Intern, AWS Elastic MapReduce
May 1, 2016 – August 1, 2016
Seattle, Washington
Cisco Systems
Software Engineering Intern, Cisco Security
August 1, 2013 – July 1, 2014
San Francisco Bay Area, USA
Cultural Fit Analysis
The candidate has worked at highly reputable, innovation-driven companies (AWS, Netflix, Cisco). Their progression into management roles suggests an ability to adapt to different organizational structures and lead teams. The focus on AI/ML platforms aligns well with modern tech culture. However, without specific project details or contributions, assessing diversity of experience beyond core ML platform development is challenging.
Soft Skills & Operational Fit
The candidate's career progression from Software Engineer to Engineering Manager at AWS and Netflix indicates strong leadership, project management, and team collaboration skills. Experience with AWS SageMaker suggests an ability to work on complex, high-impact products. However, without specific project descriptions or behavioral assessment data, a detailed analysis of soft skills and operational fit is limited.