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Machine Learning Engineer, Siri/AIML
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 am a practical researcher with statistical, machine learning, and analytic skills and experience. I think deeply, explore and validate data and models with constant curiosity, and can take a project from idea to experimentation to prototype to implementation. I'm passionate about user modeling, including recommender systems. I'm technically hands on, and have a knack for clean visualization and effective communication with stakeholders. A team player.
University of Minnesota
Ph.D., Computer Science
January 1, 2001 – January 1, 2007
Bangladesh University of Engineering and Technology
Bachelor of Science (BSc), Computer Science and Engineering
N/A – Present
Apple
Machine Learning Engineer, Siri
December 1, 2017 – Present
San Francisco Bay Area
GroundTruth
Principal ML Engineer/Scientist
August 1, 2016 – December 1, 2017
Mountain View, CA
Intel Corporation, Software & Services Group
Sr. Staff Data Scientist
January 1, 2012 – July 1, 2016
Intel Corporation, TMG/CQN
Data Miner
January 1, 2007 – January 1, 2011
Intel Research, Seattle, Washington
Research Intern
May 1, 2003 – August 1, 2003
University of Minnesota
Research Assistant
January 1, 2000 – January 1, 2007
Cultural Fit Analysis
The candidate has a long and consistent career path primarily focused on Machine Learning, Data Science, and Research within large corporations (Intel, GroundTruth, Apple). While this demonstrates stability and deep specialization, the lack of diverse project types outside of ML/Data Science and the absence of explicit backend engineering projects (beyond ML pipeline development) might indicate a narrower fit for a pure 'Backend Engineer' role, which typically requires broader system design, API development, and core application logic skills. The experience is highly specialized in ML, which may or may not align with the specific backend engineering needs of the target role.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in data analytics teams and collaboration with internal/external partners, suggesting strong operational fit and soft skills for a senior role. However, without specific psychometric test results or interview data, a definitive assessment of work attitude, stress handling, and team collaboration is not possible.