Tony Tsang
ML EngineerSenior DevOps Engineer at GoodNotes
GoodNotes
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior DevOps Engineer at GoodNotes
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Architect and construct scalable and reliable server software for serving large number of users, with complete capability of performance monitors and engineered for reliability. Actively doing development of software with software as a service (SaaS) business model for delivering software service products to customers. Specialties: Site Reliability Engineering, Linux/UNIX server side software
UNSW
Bachelor of Engineering (B.Eng.), Computer Engineering
January 1, 2000 – January 1, 2003
GoodNotes
Senior DevOps Engineer
October 1, 2021 – Present
London, England, United Kingdom · Hybrid
Kami.ai
Senior Architect - Machine Learning
November 1, 2017 – July 1, 2021
Hong Kong
IBM
Software Architect
April 1, 2009 – October 1, 2017
Hong Kong
Outblaze
Senior Software Engineer
February 1, 2007 – April 1, 2009
IBM Certified Solution Advisor - Cloud Computing Architecture V4
IBM
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning large enterprises (IBM) and startups (Kami.ai, GoodNotes, Outblaze), indicating adaptability to different organizational cultures. Their experience as a Senior Architect in Machine Learning aligns well with an ML Engineer role, suggesting a strong interest and fit within an AI-focused team. The breadth of experience from software engineering to architecture and DevOps demonstrates a versatile mindset. However, without specific project details or team interaction data, a deeper cultural fit analysis is not possible.
Soft Skills & Operational Fit
The candidate's resume indicates a strong background in senior roles, suggesting leadership, problem-solving, and operational management skills. The description of maintaining AI model inference operations and application performance analysis points to a focus on reliability and efficiency. However, without psychometric test results or interview data, a definitive assessment of soft skills and operational fit is limited.