Lead AI Cluster Models Architect

THE ROLE:

We are looking for a dynamic, energetic Lead AI Cluster Models Architect to join our growing team. As a key contributor to the success of AMD's product, you will be part of a leading team to drive and improve AMD's abilities to deliver the highest quality, industry-leading technologies to market. AMD's Systems Design Engineering team fosters and encourages continuous technical innovation to showcase successes as well as facilitate continuous career development.

THE PERSON:

The AI Cluster Models Architect plays a critical role in shaping the future of AI/ML training and inferencing systems as the AI Industry transitions into the Inference space (while still broadening within the AI Training market space). This individual will collaborate with a broad range of internal and external partners, including System management, OS, NOS, Compute Libraries, and Software Tools teams, to integrate state-of-the-art technology solutions that pave the way for AMD AI adoption within both inferencing and training.

KEY RESPONSIBILITIES:

• Designing state of the art model architectures, data, and parameter sets, for large AI/ML training and inferencing systems which can be optimized for hyperscale capabilities
• Engage with AMD customer base while aligning system and model architectures
• Pioneering system and container networking strategies to facilitate seamless operation and scaling of AI clusters
• Developing scalable AI/ML training and inferencing communication network reference architectures for each generation of AMD AI/ML products
• Participate in design phase of each AMD AI/ML GPU generation by developing cluster computational architectures and requirements
• Collaborate across AMD internal and external partner teams to improve performance for AMD AI/ML clusters

PREFERRED EXPERIENCE:

• In-depth knowledge and experience with AI clusters and topologies
• Extensive real world experience designing hyperscale computing clusters
• Strong analytical/problem-solving skills and pronounced attention to details
• Must be a self-starter, and able to independently drive tasks to completion

ACADEMIC CREDENTIALS:

• Master's or PhD degree preferred in Mathematics, Statistics, Electrical Engineering, Computer Engineering, or a related computational field; equivalent experience also considered.

Location: Could be Hybrid or remote

This role is not eligible for visa sponsorship.

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