ASIC II - AMZ9675539

Amazon•Sunnyvale, CA

15d•Onsite

About The Position

The ASIC II position at Amazon.com Services LLC involves performing architecture feasibility analysis, developing architecture specifications, and serving as a technical lead throughout the full development lifecycle, including scoping, design, development, and testing. The role requires driving technology roadmaps to foster innovation and meet the long-term product roadmap needs of Amazon Devices. This individual will work closely with Silicon and component suppliers to influence their chip roadmaps. Key responsibilities also include performing video picture quality (PQ) evaluations using industry tools and standards (ISO/IEC, VMAF, SSMI, PSNR, MOS) in both offline software simulations and a physical laboratory, and preparing training data for Machine Learning (ML) based algorithms using cloud infrastructure like AWS EC2 and S3 services for implementation into ASICs or System-on-Chips (SoCs).

Requirements

Bachelor’s degree or foreign equivalent degree in Electronic Engineering, Electrical Engineering, or a related field.
Three years of experience in the job offered or a related occupation.
One year of hands-on experience performing video picture quality (PQ) evaluations to evaluate the performance of PQ intellectual property (IP).
One year of hands-on experience with industry standard picture quality (PQ) evaluation tools and standards including ISO/IEC, VMAF, SSMI, PSNR, and MOS.

Responsibilities

Perform architecture feasibility analysis and make recommendations.
Develop architecture specifications.
Serve as technical lead throughout the full development lifecycle, from scoping, design, development, and testing.
Drive technology roadmaps in areas of expertise to drive innovation and meet the needs of the long term Amazon Devices’ product roadmap.
Work closely with Silicon and component suppliers to influence their chip roadmaps to meet needs.
Perform video picture quality (PQ) evaluations to evaluate the performance of PQ intellectual property (IP) using industry tools and standards (ISO/IEC, VMAF, SSMI, PSNR, MOS) in both offline software simulations and in a physical laboratory.
Prepare training data for Machine Learning (ML) based algorithms using cloud infrastructure such as AWS EC2 and S3 services in preparation for implementation into a ASIC or System-on-Chip (SoC).