Amit Sharma Email & Phone Number | An accomplished QA and test automation engineer with experience in build and release automation. -Test automation using Python, Java, Selenium Webdriver and Appium. -Worked with tools like Git, Gerrit, Docker and Jenkins for continuous integration and deployment. -Software deployment in traditional and cloud environments. -Developed test plan and test suites for stress, stability, performance, power and functionality of embedded devices, web and mobile applications. -Build Machine Learning models and Deep Learning models for academic projects during Master's in Software Engineering. Technical skills: -DevOps Technologies: AWS, Docker, Kubernetes, Jenkins, Nexus, Git, Gerrit, -Test Automation Technologies: Selenium Web Driver, Appium, JUnit, TestNG -Programming Languages and Scripting: Python, Java, JavaScript, Shell -Database: MySQL, Oracle, MongoDB, -Data Science Technologies: NumPy, Pandas, Scikit-learn, Matplotlib, NLTK, TimeSeries modeling, TensorFlow, Keras, PyTorch

Amit Sharma

An accomplished QA and test automation engineer with experience in build and release automation. -T...
Fremont, California, United States

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Amit Sharma’s Email amitsharma@nvidia.com

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Amit Sharma’s Location Fremont, California, United States

Amit Sharma’s Current Industry Nvidia

Amit Sharma’s Prior Industry Hcl Technologies | Cisco | Nokia

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Sr. MLOps Engineer

2022-01-01 00:00:00 - Present

Senior Techanical Lead

2016-08-01 00:00:00 - 2019-12-01 00:00:00

Senior Test Automation Engineer

2016-01-01 00:00:00 - 2016-08-01 00:00:00

System Software Engineering

2006-02-01 00:00:00 - 2010-03-01 00:00:00

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Amit Sharma is a An accomplished QA and test automation engineer with experience in build and release automation. -Test automation using Python, Java, Selenium Webdriver and Appium. -Worked with tools like Git, Gerrit, Docker and Jenkins for continuous integration and deployment. -Software deployment in traditional and cloud environments. -Developed test plan and test suites for stress, stability, performance, power and functionality of embedded devices, web and mobile applications. -Build Machine Learning models and Deep Learning models for academic projects during Master's in Software Engineering. Technical skills: -DevOps Technologies: AWS, Docker, Kubernetes, Jenkins, Nexus, Git, Gerrit, -Test Automation Technologies: Selenium Web Driver, Appium, JUnit, TestNG -Programming Languages and Scripting: Python, Java, JavaScript, Shell -Database: MySQL, Oracle, MongoDB, -Data Science Technologies: NumPy, Pandas, Scikit-learn, Matplotlib, NLTK, TimeSeries modeling, TensorFlow, Keras, PyTorch