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Intern Software Engineer Gpu Jobs in California (NOW HIRING)

Software Engineer, GPU

Mountain View, CA ยท On-site

$204K - $259K/yr

In this hybrid role, you will report to a Senior Software Engineer. You will: * Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across ...

We are seeking a System Software Engineer to work on next-generation computing and graphics products. Our charter is to build low level GPU testing frameworks to validate GPUs early in the life cycle.

Senior Software Engineer, GPU Performance

Sunnyvale, CA ยท On-site

$143K - $188K/yr

They are seeking a Senior Software Engineer to optimize GPU performance for critical products, driving innovations in AI and accelerated computing. Responsibilities : โ€ข Build optimizations for the ...

Senior Software Engineer, GPU Performance

Sunnyvale, CA ยท On-site

$143K - $189K/yr

Experience with compiler optimization, code generation, and runtime systems for GPU architectures (OpenXLA, MLIR, Triton, etc.). About the job Google's software engineers develop the next-generation ...

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Intern Software Engineer Gpu information

What is the difference between Intern Software Engineer Gpu vs Intern Software Engineer Cloud?

AspectIntern Software Engineer GpuIntern Software Engineer Cloud
Required CredentialsComputer Science degree or related, programming skills, familiarity with GPU programmingSimilar credentials, with emphasis on cloud platforms and networking
Work EnvironmentHardware-focused, GPU development labs, research teamsCloud infrastructure, remote teams, data centers
Employer & Industry UsageTech companies, hardware manufacturers, AI researchCloud service providers, SaaS companies, enterprise IT

Intern Software Engineer Gpu roles focus on GPU hardware and software development, often involving parallel computing and AI workloads. Intern Software Engineer Cloud positions emphasize cloud infrastructure, deployment, and scalability. Both roles require strong programming skills and industry knowledge but differ mainly in their technical focus and work environment.

What are the most commonly searched types of Software Engineer Gpu jobs in California? The most popular types of Software Engineer Gpu jobs in California are:
What cities in California are hiring for Intern Software Engineer Gpu jobs? Cities in California with the most Intern Software Engineer Gpu job openings:

GPU Software Engineer/GPU Architect

Triune Infomatics Inc

San Jose, CA โ€ข On-site

$164K - $202K/yr

Other

Re-posted 6 days ago


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