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
De La Salle University
Master of Science - MS, Computer Science
January 1, 2018 – January 1, 2021
University of Santo Tomas
Bachelor’s Degree, Computer Science
January 1, 2013 – January 1, 2018
University of Santo Tomas
High School
January 1, 2009 – January 1, 2013
Rakuten
Machine Learning Engineer
October 1, 2024 – Present
Tokyo, Japan
ShipServ
Machine Learning Engineer
August 1, 2023 – June 1, 2024
National Capital Region, Philippines
Maya
Lead Machine Learning Engineer
April 1, 2022 – August 1, 2023
National Capital Region, Philippines
meldCX
Machine Learning Engineer
August 1, 2020 – April 1, 2022
Senti AI
Machine Learning Engineer
April 1, 2018 – August 1, 2020
Makati, Philippines
AELOGICA
Intern
June 1, 2017 – July 1, 2017
Bonifacio Global City, Philippines
Professional Cloud Architect
Google Cloud
June 24, 2026 – Present
Professional Data Engineer
Google Cloud
June 24, 2026 – Present
Associate Cloud Engineer
Google Cloud
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked across various companies (Rakuten, ShipServ, Maya, meldCX, Senti AI), indicating adaptability to different organizational cultures. The consistent focus on Machine Learning Engineer roles aligns well with the target role. However, without project details, it's difficult to assess diversity in problem-solving approaches or specific contributions to team environments. The absence of personal projects or community involvement limits the assessment of broader cultural engagement.
Soft Skills & Operational Fit
The candidate's career progression from ML Engineer to Lead ML Engineer suggests strong operational fit and potential for leadership. The lack of specific project descriptions or psychometric test results prevents a detailed assessment of soft skills like teamwork, communication clarity, or stress handling.