CVP of Applied AI FDE
AMD · San Jose, CA · Engineering
About this role
AMD is hiring a vp-level AI Engineer in the machine learning function based in San Jose, CA. The posting calls out experience with CUDA, Kubernetes, Docker, TensorFlow.
- Role
- AI Engineer
- Function
- machine learning
- Level
- vp
- Track
- Individual contributor
- Location
- San Jose, CA
- Visa
- Not sponsored
- Department
- Engineering
- Posted
- Jan 13, 2026
More roles at AMD
Job description
from AMD careersWHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
This role is not eligible for visa sponsorship.
THE ROLE:
Build and scale a world-class FDE organization, strategically combining ML Generalists, Low-Level Kernel Optimizers, and Solutions Architects to cover the full customer deployment lifecycle. This is a highly visible role with large scope and impact.
THE PERSON:
Define and institutionalize the FDE Engagement Model to maximize resource leverage and ensure consistent, high-velocity customer outcomes. Serve as the Voice of the Customer internally: Translate field intelligence and customer challenges into concrete, prioritized engineering roadmaps, and ensure execution.
KEY RESPONSIBILITIES:
- Cluster Bring-up & Optimization: Oversee the technical onboarding of massive GPU clusters. Ensure your team can troubleshoot collective communication errors, debug framework issues, and optimize training/inference strategies.