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Contract 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

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 ...

THE ROLE We're seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state‑of‑the‑art machine learning ...

Principal Software Engineer, GPU Compute

San Mateo, CA · On-site

$153K - $206K/yr

As a Principal Software Engineer on the Compute team, you will be the technical anchor for Roblox's GPU and AI accelerator capabilities. This is a battle-tested GPU expert role focused on the machine ...

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Contract Software Engineer Gpu information

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$63.5K

$147.5K

$205.5K

How much do contract software engineer gpu jobs pay per year?

As of Sep 8, 2026, the average yearly pay for contract software engineer gpu in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

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

AspectContract Software Engineer GpuContract Software Engineer Cloud
Required CredentialsProficiency in GPU programming, CUDA, OpenCLExperience with cloud platforms, APIs, and cloud-specific tools
Work EnvironmentDeveloping high-performance GPU applications, often on specialized hardwareBuilding and deploying applications on cloud infrastructure, remote environments
Employer & Industry UsageTech companies, AI, gaming, scientific computingCloud service providers, SaaS companies, enterprise solutions
Search & Comparison IntentLooking for GPU-focused software engineering rolesSeeking cloud-based software engineering opportunities

The main difference between Contract Software Engineer Gpu and Contract Software Engineer Cloud lies in their focus areas. GPU roles emphasize high-performance computing and specialized hardware, while cloud roles focus on deploying and managing applications in cloud environments. Both require strong software development skills, but their tools and work settings differ significantly.

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Infographic showing various Contract Software Engineer Gpu job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

GPU Software Engineer/GPU Architect

Triune Infomatics Inc

San Jose, CA • On-site

$164K - $202K/yr

Other

Re-posted 15 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