1

Contract Software Engineer Gpu Jobs in California

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 ...

System Software Engineer - GPU

Santa Clara, CA ยท On-site

$203K - $240K/yr

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 ...

San Jose, CA Duration: 6+ months contract (Long Term) Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early Architectural planning process ...

next page

Showing results 1-20

Contract Software Engineer Gpu information

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.

How much does a contract software engineer Gpu make?

A contract software engineer specializing in GPU development typically earns between $50 and $150 per hour, depending on experience, location, and project complexity. Senior engineers with specialized skills in CUDA, OpenCL, or similar tools may command higher rates, especially for short-term or high-demand projects.
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 Contract Software Engineer Gpu jobs? Cities in California with the most Contract 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 13 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