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Machine Learning Engineer at Apple
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced Software Engineer with a demonstrated history of working in the Ad tech industry. Skilled in C, Java, python, Machine Learning, Software Development, and SQL. Strong engineering professional with a Master's Degree focused in Computer Science(AI) from State University of New York at Buffalo.
University at Buffalo
Master's Degree, Computer Science
January 1, 2013 – January 1, 2014
International Institute of Information Technology Hyderabad (IIITH)
Bachelor's of Technology, Computer Science
January 1, 2007 – January 1, 2011
Apple
Machine Learning Engineer
October 1, 2017 – Present
cupertino
Adap.tv
Software Engineer
January 1, 2016 – September 1, 2017
San Mateo
Neptune.io
Software Engineer
May 1, 2014 – January 1, 2016
San Mateo
IIIT Hyderabad
Assistant programmmer
July 1, 2012 – July 1, 2013
Greater Hyderabad Area
Burning Glass Technologies
Advanced Software Engineer
June 1, 2011 – July 1, 2012
Greater Chennai Area
Fingerprint search engine (java)
December 1, 2014 – Present
Implemented a novel indexing and search scheme for Fingerprints. Narrowed the search space to less than 1% of data-set in logarithmic time complexity.
Face recognition
May 1, 2014 – Present
Implemented Fisher-faces and Eigen-faces face recognition algorithms. Demonstrated that the “Fisherface” method has error rates lower than those of the Eigen-face technique on the Harvard and Yale Face Databases.
SQL Query Evaluator (Java)
January 1, 2014 – May 1, 2014
Developed a SQL query engine using JSqlParser to evaluate queries efficiently on a given set of data by generating optimized query plans and to display the output in a standardized form.
Hand Written Digit Recognition(Matlab)
December 1, 2013 – Present
Implemented classification algorithms to recognize Hand written digits. Compared the accuracy of Neural Networks and Logistic regression based models.
Multi Threaded Web Server (C, Linux)
December 1, 2013 – Present
Implemented version 1.0 of HTTP, as defined in RFC 1945, where separate HTTP requests are sent for each component of the Web page. The server will be able to handle multiple simultaneous service requests in parallel. Avoided busy wait of worker threads using semaphores.
Info-box filling and Search engine for wikipedia documents (Java)
April 1, 2010 – Present
Developed a model for extracting and filling the infobox attributes of wiki documents. As a part of the project, implemented a complete search engine on wiki documents. Technologies used: Sax parser, Stanford Named Entity tagge
Cultural Fit Analysis
The candidate has a diverse project background, including personal projects in machine learning, search engines, and web servers, indicating a broad technical interest. Professional experience spans machine learning, ad-tech, and event automation platforms. While the target role is 'Backend Engineer', the recent experience at Apple as a 'Machine Learning Engineer' suggests a potential shift in focus. The breadth of skills and project types indicates adaptability, but the alignment with a pure backend role needs further validation.
Soft Skills & Operational Fit
The candidate's experience descriptions suggest a focus on problem-solving, system optimization, and taking ownership (e.g., auditing and re-writing test suites). The project descriptions indicate an analytical and research-oriented approach. However, direct evidence of collaboration, stress handling, or specific communication styles is not available from the provided data.