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GPU Software Engineer/GPU Architect

Triune Infomatics IncSan Jose, CA🇺🇸United StatesPosted 9 Jul 2026

Why This Role Stands Out

This role offers an exciting opportunity to shape the future of AI and GPU technologies, contributing to cutting-edge semiconductor advancements. You'll thrive here if you possess deep expertise in GPU architecture, CUDA/ROCm kernel development, and inference systems, eager to collaborate in a dynamic, on-site team environment. Apply now to leverage your skills and drive innovation in high-performance computing.

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Role: GPU Software Engineer/GPU Architect
Location: San Jose, CA (Remote/Hybrid)
Duration: Long-term >> ongoing contract
 
Overview: We''re looking for a strong GPU Software Engineer/GPU Architect to join a highimpact engineering team working on nextgeneration AI, GPU, and semiconductor technologies. This role focuses on GPU kernel development, memory architecture, and integration with modern inference systems such as vLLM and SGLang. You''ll work onsite in San Jose, collaborating closely with a team of engineers building highperformance GPUaccelerated systems.
  • Develop and optimize CUDA/ROCm kernels for AI workloads
  • Work with HBM, memory hierarchy, thread scheduling, and P2P communication
  • Integrate GPU kernels with vLLM, SGLang, and other inference servers
  • Build highperformance components in C++ and Python
  • Support AI frameworks such as PyTorch and TensorFlow
  • Optimize multiGPU scaling, KVcache, and attention kernels
  • Profile and debug GPU workloads using Nsight, rocprof, etc.
  • Collaborate with crossfunctional GPU, AI, and semiconductor teams
Required Skills:
  • Strong experience with CUDA, ROCm/HIP, OpenCL, or MPI
  • Deep understanding of GPU architecture, HBM, memory models, and thread hierarchies
  • Handson experience with AMD/NVIDIA GPU software stacks
  • Expertlevel C++ and Python
  • Experience with PyTorch or TensorFlow
  • Experience with vLLM, SGLang, or similar inference systems
Preferred Skills:
  • RDMA, RoCE, InfiniBand, or Infinity Fabric
  • Distributed inference/training or HPC experience
  • Semiconductor or hardwareadjacent experience

Skills

CUDA
C++
PyTorch
Python
TensorFlow

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