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Intern Software Engineer Gpu Jobs (NOW HIRING)

Expertise in C++ programming for GPU (CUDA or similar framework) * Bachelor degrees in EECS, coupled with a minimum of five years of industry experience * Solid understanding of GPU software stack

Software Engineer, GPU

Mountain View, CA · On-site

$204K - $259K/yr

Expertise in C++ programming for GPU (CUDA or similar framework) * Bachelor degrees in EECS, coupled with a minimum of five years of industry experience * Solid understanding of GPU software stack

Intern, Software Engineer Job Code: 42893 Job Location: Palm Bay, FL Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off We are ...

Intern, Software Engineer Job ID: 42277 Job Location: Palm Bay, FL Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off The Embedded ...

As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced ...

Intern, Software Engineer Job Code: 43512 Job Location: Northampton, MA Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off * Apply ...

Intern, Software Engineer Job Code: 43513 Job Location: Northampton, MA Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off * Apply ...

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Intern Software Engineer Gpu information

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How much do intern software engineer gpu jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for intern software engineer gpu in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

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.

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GPU Software Engineer/GPU Architect

San Jose, CA • On-site

Triune Infomatics Inc
IT Services • 51 - 200 employees

$164K - $202K/yr

Other

Re-posted 18 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