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Staff 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
I build large scale ML systems for all the things that LLMs aren't great at (yet?) - ranking, recommendations, search/retrieval, fraud/risk prediction..
University of California, Davis
Doctor of Philosophy (Ph.D.), Physics
January 1, 2009 – January 1, 2015
University of Maryland
Bachelor’s Degree, Physics and Mathematics
January 1, 2006 – January 1, 2009
Coinbase
Staff Machine Learning Engineer
February 1, 2024 – Present
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Chegg Inc.
Senior Data Scientist
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Chegg Inc.
Data Scientist - Machine Learning
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Sqor Sports
Lead Data Scientist
June 1, 2016 – July 1, 2016
Sqor Sports
Data Scientist
January 1, 2016 – June 1, 2016
UC Davis
Graduate Student Researcher
January 1, 2012 – January 1, 2015
University of Maryland
Undergraduate Researcher
January 1, 2007 – January 1, 2009
Cultural Fit Analysis
The candidate has a strong background in data science and machine learning across multiple companies, indicating adaptability and a drive for career progression. However, the target role is 'Backend Engineer', which is a significant shift from their primary experience. While ML engineers often have backend skills, the resume does not explicitly detail backend engineering projects or specific technologies relevant to a pure backend role. This lack of direct alignment with the target role suggests a moderate cultural fit, as the candidate's core expertise is in a related but distinct domain.
Soft Skills & Operational Fit
The candidate's career progression from Data Scientist to Staff Machine Learning Engineer suggests strong problem-solving, leadership, and continuous learning abilities. However, without specific project descriptions or interview data, it is difficult to assess communication, teamwork, and stress handling directly. The psychometric and English test scores are not provided, limiting assessment in these areas.