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Machine Learning Software 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
Specialties: Machine learning generalist, recommender systems/search expert. Deep knowledge of large language models and their production serving. Extensive experience in developing ML models and scalable infrastructure to support ultra-high QPS. US permanent resident
The Australian National University
Doctor of Philosophy (PhD), Machine Learning
January 1, 2012 – January 1, 2016
Tubi
Staff Machine Learning Engineer (Tech Lead)
March 1, 2023 – Present
San Francisco Bay Area · Remote
Machine Learning Engineer
January 1, 2018 – January 1, 2023
San Francisco, California, United States
Tabcorp
Data Scientist
October 1, 2016 – December 1, 2017
Sydney, Australia
Adobe
Data Scientist Intern
August 1, 2015 – June 1, 2016
San Jose
Kobo Inc.
Big Data Intern
December 1, 2013 – March 1, 2014
Greater Toronto Area, Canada
Australian National University / NICTA
PhD Student
August 1, 2012 – July 1, 2016
Logpoint
Software Engineer
May 1, 2010 – June 1, 2012
Bikalpa
Developer
July 1, 2009 – July 1, 2010
Cultural Fit Analysis
The candidate has a strong background in Machine Learning Engineering and Data Science across various companies (Tubi, Twitter, Tabcorp, Adobe, Kobo Inc.). While the experience is diverse in terms of companies, the core focus has consistently been on ML, particularly recommender systems and personalization. The target role of 'Data Analyst' is a significant mismatch with the candidate's extensive and advanced ML engineering background. This indicates a potential cultural misalignment if the role is strictly data analysis without ML model development or research components.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership (Tech Lead, driving initiatives, co-led, mentored) and collaboration (co-owned, onboarding engineers). This suggests strong soft skills relevant for senior roles. The operational fit for a Data Analyst role is not direct, as the experience is heavily skewed towards Machine Learning Engineering and research, which typically involves more model building and deployment than pure data analysis.