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Senior Machine Learning Developer
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Shandong Jianzhu University
Bachelor's degree, Electrical Engineering and Automation
January 1, 2011 – January 1, 2015
SAS
Senior Machine Learning Developer
June 1, 2017 – Present
Raleigh-Durham-Chapel Hill Area · Remote
Shandong HCTL IOT Science and Technology Co., Ltd.
Software Engineer
December 1, 2014 – July 1, 2015
Jinan, Shandong
Shanda Huatian Technology Co., Ltd
Assistant of equipment commissioning engineer
January 1, 2014 – February 1, 2014
Jinan, Shandong
Grass Management and Maintenance Internet of Things Product
October 1, 2016 – Present
Developing an IOT product which helps people monitor and manage yards based on type of grasses, soil condition and weather condition. Provide maintenance strategy based on user preference and big data. Implemented on IBM Bluemix and AWS cloud platform. Used Zigbee as wireless communication method between Gateway (Raspberry Pi) and end device (Arduino).
Boston House Prices Prediction
September 1, 2016 – December 1, 2016
Performed innovative project focusing on Machine Learning for Boston house prices dataset. Analyzed and clean dataset with 79 explanatory features and generated synthetic features from raw data. Applied machine learning models including Lasso and Ridge Regression, SVM, Gradient Boosting models in Python.
Enhancing Floating Touch base on Contacting Touch Model
May 1, 2016 – Present
• A research Implemented an algorithm to fix floating touch gesture based on the most similar contacting touch gesture stored in gesture database. • Researched on gesture features and evaluated the performance based on 9 types of common gestures. • Implemented the App with API including Webview, gesture, canvas, SQLite, etc.
User Authentication Android Application based on Gesture
January 1, 2016 – May 1, 2016
• An Android project in which phone owner could easily unlock screen while potential attackers are hard to pass even if the attackers attempt to duplicate true user’s gesture. The App provides the smartphone without fingerprint sensor with a secure authentication. • Created a gesture recognition algorithm based on pattern recognition and machine learning techniques • Used a wide variety of sensors and Android APIs: e.g., gyroscope, accelerometer, screen pressure, gesture. • Built up the database for the App using SQLite.
Smart Irrigation System
September 1, 2015 – December 1, 2015
• An embedded system project in which, given specific yard details and humidity of soil, create accurate schedules customized to the particular needs of yard. • Developed a RESTful web application provided for Android and Arduino to access. • Adjust the sprinkler system and display historical records on Android App. • Built up the database for this web application using MySQL.
Cultural Fit Analysis
The candidate's project portfolio is diverse, spanning machine learning, mobile development, and IoT/embedded systems. While this demonstrates versatility, the direct alignment with a 'FPGA Developer' role is limited. The projects show an interest in hardware interaction (Arduino, Raspberry Pi, Zigbee) but lack explicit FPGA or ASIC design experience. The professional experience as a 'Senior Machine Learning Developer' further diverges from the target role. This suggests a potential mismatch in core expertise for a dedicated FPGA role, though the foundational electrical engineering background is relevant.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving approach and an ability to work on diverse technical challenges. The experience in developing user-facing applications and embedded systems suggests a practical, results-oriented mindset. However, without psychometric test results, a full assessment of work attitude, stress handling, and team collaboration is not possible.