Advanced Micro Devices, Inc

CVP of Applied AI FDE

Advanced Micro Devices, Inc$180K — $220K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of leadership in high-impact technical teams, particularly in Cloud Infrastructure or AI Platform environments.
  • Strong understanding of both hardware and software components in computing systems.
  • Familiarity with commercial metrics such as ARR and Churn to align technical solutions with business impact.
  • Proven crisis management capabilities with experience in high-stakes incidents, particularly in AI or HPC contexts.
  • Technical proficiency with AI frameworks like PyTorch, JAX, TensorFlow, and distributed computing tools like Kubernetes.

Responsibilities

  • Oversee technical onboarding of GPU clusters, ensuring troubleshooting and optimization of frameworks.
  • Drive customer GPU utilization across massive clusters as the primary success metric.
  • Optimize deployment of open-source and proprietary AI models for specific hardware.
  • Act as technical authority for significant deals, collaborating with executive leadership.
  • Channel feedback from customers to product engineering for continuous improvement.

Benefits

  • Comprehensive health plans including medical, dental, and vision.
  • Retirement savings plans with company match.
  • Flexible work hours and remote work options.
  • Generous paid time off and holidays.
  • Employee development programs and tuition assistance.
Full Job Description
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.
  • Utilization Engineering (The North Star Metric): Drive and maintain industry-leading Customer GPU Utilization across clusters of thousands of GPUs, making cluster satisfaction the key measure of success.
  • High-Performance Model Deployment: Enable customer success by deeply optimizing open-sourced models (Llama 3, DeepSeek, Mixtral) and proprietary models for our specific hardware topology, utilizing tools like vLLM and TensorRT-LLM.
  • Executive Technical Sponsorship: Act as the technical authority and executive sponsor on large deals, possessing the credibility to validate architecture with CTOs and VPs of AI.
  • Feedback Loop: Aggressively channel field intelligence back to Product Engineering. If customers are struggling with a specific use case, then become the loudest voice in the room demanding a fix.


PREFERRED EXPERIENCE:

  • Years of Technical Leadership: Demonstrated track record leading high-impact technical teams within high-stakes environments (e.g., Cloud Infrastructure, AI Platform, or HPC).
  • The "Hardware/Software" Hybrid: You understand the stack from the metal up.
  • Commercial Acumen & Fluency: Deep understanding of commercial drivers (ARR, Churn, Margin) and the ability to articulate how technical solutions impact deal velocity and business outcomes.
  • High-Stakes Crisis Management: Experience leading through "Sev0" customer incidents (e.g., massive training run failures), demonstrating the poise and clarity required to manage executive communication while guiding rapid root cause resolution.


Technical Competency

  • AI Frameworks: PyTorch, JAX, TensorFlow.
  • Distributed Computing: Slurm, Ray, Kubernetes (K8s), Docker.
  • GPU Ecosystem: NVIDIA drivers, CUDA profiling (Nsight Systems), Triton Inference Server.
  • LLM Operations (Differentiator): Significant experience with advanced LLM deployment and customization techniques, including fine-tuning (e.g., LoRA/QLoRA) and building RAG pipelines.


ACADEMIC CREDENTIALS:
  • BS, MS or equivalent with direct experience


#LI-MH2

Benefits offered are described: AMD benefits at a glance.

About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ

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