Posted 1mo ago

Principal Product Manager, GPUs and AI Accelerators

@ Code Metal
Washington, District of Columbia, United States
HybridFull Time
Responsibilities:Own strategy, Define GPUs, Engage customers
Requirements Summary:5+ years in product management or technical leadership in GPUs/AI accelerators; experience with CUDA/ROCm/OpenCL; AI frameworks like PyTorch; strong communication and discovery skills; US Citizenship.
Technical Tools Mentioned:CUDA, ROCm, OpenCL, PyTorch, OpenCV
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Job Description

Code Metal is redefining code translation for mission-critical industries. We build code-to-code translation platforms that help commercial and defense partners across AI, advanced signal processing and HPC move quickly and reliably from algorithm to silicon. Our platform accelerates deployment of performance-critical AI and Signal-Processing workloads to a host of compute platforms including GPUs and domain specific accelerator ASICs. 

We are hiring a Principal-level Technical Product Manager for GPUs and AI Accelerators, who will be a critical part of defining a new programmability paradigm for our customers who build GPUs and AI Accelerators.

The Role

This is a leadership role that exists to produce a clear outcome:

Code Metal has a clear product roadmap for supporting accelerated development and deployment of AI, Image Processing and Signal Processing applications on the most commonly used GPUs (edge or data-center) and AI accelerator hardware. 

You will work directly with customers, engineers, and growth leaders to identify source languages, target languages and hardware target platforms for applying Code Metal’s verified code translation technology.

Success is measured by clarity, and time-to-impact.

Responsibilities:

  • Own product strategy and roadmap for code translation pipelines focused on programmability of GPUs and AI accelerator platforms. 
  • Define and prioritize the GPUs and variants (NPU, Vector-Processors, IPU, AI accelerators) to target for accelerated deployment
  • Engage directly with commercial and defense customers to understand how they evaluate, adopt, accredit, and scale new technology
  • Combine customer and end-user needs with technical feasibility to shape functional specifications, user stories, and success metrics
  • Identify patterns across customer engagements that inform platform capabilities rather than one-off solutions