Software Development Engineer - Computer Vision Frameworks/Acceleration
1 week ago(8/13/2018 4:07 PM)
A2Z Development Center, Inc.
Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?
As a Computer Vision Frameworks/Acceleration Engineer, you will work in one of the most exciting engineering domains alongside subject matter experts and technology partners. You must love software development, have a strong interest in Computer Vision, and have a passion for creating and learning new concepts or domains. As part of a technology team, your work will have a large impact on hardware, internal software, ecosystem, and ultimately the lives of Amazon customers.
Some of your key responsibilities include: - Develop frameworks for Computer Vision processing - Integrate Computer Vision processing with media streaming frameworks - Analyze and optimize complex use cases for best performance and power - Develop benchmarks and use cases to define next generation SoCs and HW product
- Bachelor’s degree in Computer Science or related field - 3+ years of software engineering with full development life cycle - 3+ years of recent C/C++ programming and debugging skills, at least 1 year in C++ - 2+ years of applying object oriented design principles
- Master’s degree in Computer Science or related field - Experience in GPU programming and performance tuning, ideally using OpenCL - Experience in CPU performance analysis and optimization - System use cases analysis and prediction of performance and power - Knowledge of Android multimedia frameworks - Knowledge of open source multimedia frameworks (e.g. GStreamer) - Domain knowledge of Computer Vision and/or Machine Learning - Strong communication and team collaboration skills