Senior Director, GPU Platform & AI Compute Strategy

Qualcomm Incorporated; San Diego (CA); On-site; USD 238,000 - 357,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a visionary product leader to own the GPU platform strategy for AI-centric data center, edge, and mobile workloads.

You will drive end-to-end lifecycle from architecture to commercialization, partnering with AI, CPU, and system teams to advance heterogeneous computing and differentiated platform features. The role requires deep GPU hardware knowledge, 10+ years in product management or related areas, and leadership experience in large matrixed

Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related technical field.
• 10+ years of Product Management or related work experience.

Responsibilities

• Own the end-to-end GPU platform product strategy and lifecycle—from architectural definition through commercialization with emphasis on the datacenter.
• Guide the development of next-generation GPU capabilities spanning AI acceleration and power-efficient system integration.
• Serve as the central product leadership for GPU platforms across architecture, hardware, software, tools, and ecosystem teams.
• Define and execute multi-year GPU technology strategy and roadmaps for AI-centric data center platforms and rack-level systems.
• Drive engagement with developers, ISVs, OEMs, and strategic partners for enablement and tooling.
• Partner with business unit leadership to derive crisp product requirements, craft market positioning, launch plans and GTM collateral.

Skills

GPU hardware

Product management

Leadership

System-level platforms

AI acceleration

Education

Bachelor's degree in Engineering/CS/IS

Tools

TensorFlow

PyTorch

Job description

Qualcomm Technologies, Inc. is seeking a visionary product leader to own the GPU platform strategy for AI-centric data center, edge, and mobile workloads.

You will drive end-to-end lifecycle from architecture to commercialization, partnering with AI, CPU, and system teams to advance heterogeneous computing and differentiated platform features. The role requires deep GPU hardware knowledge, 10+ years in product management or related areas, and leadership experience in large matrixed