Product Manager, AI Platform Kernels And Communication Libraries

at Nvidia
📍 Santa Clara, United States
USD 144,000-258,800 per year
MIDDLE
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

GitHub @ 3 Algorithms @ 3 Communication @ 3 Product Management @ 5 CUDA @ 3 GPU @ 3

Details

NVIDIA's AI Software Platforms team is seeking a technical product manager to accelerate next-generation inference deployments through innovative libraries, communication runtimes, and kernel optimization frameworks. The role bridges low-level GPU programming with ecosystem-wide developer enablement for products such as CUTLASS, cuDNN, NCCL, NVSHMEM, and open-source contributions to Triton and FlashInfer.

Responsibilities

  • Architect developer-focused products that simplify high-performance inference and training deployment across diverse GPU architectures.
  • Define the multi-year strategy for kernel and communication libraries by analyzing performance bottlenecks in emerging AI workloads.
  • Collaborate with CUDA kernel engineers to design intuitive, high-level abstractions for memory and distributed execution.
  • Partner with open-source communities like Triton and FlashInfer to shape and drive ecosystem-wide roadmaps.

Requirements

  • 5+ years of technical product management experience shipping developer products for GPU acceleration, with expertise in HPC optimization stacks.
  • Expert-level understanding of CUDA execution models and multi-GPU protocols.
  • BS or MS or equivalent experience in Computer Engineering or demonstrated expertise in parallel computing architectures.
  • Strong technical interpersonal skills with experience communicating complex optimizations to developers and researchers.

Ways to Stand Out

  • PhD or equivalent experience in Computer Engineering or related fields.
  • Contributions to performance-critical open-source projects like Triton, FlashAttention, or TVM.
  • Crafted GitHub-first developer tools with significant community engagement.
  • Published research related to GPU kernel optimization, collective communication algorithms, or ML model serving architectures.
  • Experience building cost-per-inference models incorporating hardware utilization, energy efficiency, and cluster scaling factors.

Salary and Benefits

  • Base salary range: 144,000 USD - 258,750 USD per year.
  • Eligibility for equity and benefits.
  • NVIDIA is an equal opportunity employer committed to diversity.