Systems Design Engineer - DC GPU Validation (Test Automation)

at  Advanced Micro Devices Inc

PREFERRED EXPERIENCE:

• Proven track record of developing Python and other object-oriented based solutions in a team environment.
• Power user of Linux, Docker, Kubernetes, containers, etc.
• Experienced with creating modular and maintainable code adhering to best practices.
• Experience with debugging and setting up computer and network hardware.
• Software and hardware test + debug experience.
• Experience with other languages, web development, REST and databases is an asset.
• Experience in data analytics and report generation is an asset.
• Experience in cross OS development in Linux and windows environment preferred.
• Familiar with source controls systems like GitHub, Perforce and SVN.

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
AMD together we advance_
Responsibilities:

THE ROLE:

Our growing team plays a major role in architecting and shaping every GPU offered by AMD. As part of the Datacenter GPU Validation team, you will be involved in designing, enhancing and supporting manufacturing automation infrastructure and content used to validate datacenter GPU/CPU hardware and software. Your work will enable various validation teams to improve their processes through developing new automation features, or by helping debug or co-create their automated test content.

KEY RESPONSIBILITIES:

• Design, develop and support in-house automation and infrastructure solutions that can reliably at scale over large part test distributions.
• Engage multi-disciplinary stakeholders for requirement gathering and issue resolving.
• Develop deep understanding of upcoming AMD SOCs, IPs, tools, and programming libraries to create relevant and cohesive solutions.