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Contract Software Engineer Gpu Jobs (NOW HIRING)

Baseten

Software Engineer - GPU Fabric Observability

New York, NY · On-site

$200K - $380K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The ...

Fluidstack

Software Engineer, GPU Infrastructure

San Francisco, CA · On-site

$203K - $241K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... software. Speed and scale are our key differentiators. Come be a part of building civilization ... The Production Engineering Team Examples of key exciting problems the team is working on * Build ...

Google

Senior Software Engineer, GPU Performance

Sunnyvale, CA · On-site

$143K - $189K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Fluidstack

Software Engineer, GPU Infrastructure

San Francisco, CA · On-site

$208K - $269K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... software. Speed and scale are our key differentiators. Come be a part of building civilization ... The Production Engineering Team Examples of key exciting problems the team is working on * Build ...

Xoriant Corporation

GPU Software Engineer

San Jose, CA · On-site

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 ...

Nebius

Lead Software Systems Engineer - GPU Performance

  • Medical

  • Dental

  • Vision

  • Retirement

We are looking for a Lead Software Systems Engineer - GPU Performance to play a key role in building our hyperscaler platform, working across its core components while analyzing and optimizing the ...

Xoriant Corporation

GPU Software Engineer

Austin, TX · On-site

Austin, TX Duration: Long Term Contract Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early Architectural planning process until we ...

Xoriant Corporation

GPU Software Engineer

Austin, TX · On-site

Austin, TX Duration: Long Term Contract Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early Architectural planning process until we ...

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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 Aug 18, 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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Contract Software Engineer Gpu jobs near you
Infographic showing various Contract Software Engineer Gpu job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 8% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

Software Engineer- GPU/AI/ML

AMD (Advanced Micro Devices)

Santa Clara, CA • On-site

Other

Posted 4 days ago

Advanced Micro Devices rating

8.6

Company rating: 8.6 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

27th of 159 rated electronics manufacturers

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
WHY AMD
At AMD, we build products that accelerate next-generation computing-from AI and data centers to PCs, gaming, and embedded systems. Progress here comes from bold ideas, strong execution, and people who care about hard problems.
This role sits at the center of that mission: making AMD the platform of choice for the most demanding AI workloads by improving how models train, align, and run on our GPUs.
THE OPPORTUNITY
We're looking for a senior software engineer who combines deep systems performance work with modern AI-someone who can shape software from GPU kernels through distributed training and inference.
You'll join a core team of specialists working on the latest AMD hardware and software. Your work will directly influence the ROCm ecosystem and how foundation models and agentic systems perform on AMD GPUs.
The challenge: Help train and run AI systems that make AI itself more efficient on GPUs-tuning stacks, kernels, and workflows in ways that can materially shift what's possible on our hardware.
This is a high-impact, hands-on role. You'll own hard technical problems, influence direction across teams, and mentor others as we scale AMD's AI software strategy.
WHAT YOU'LL DO
  • Own the AI software stack: Establish best practices and drive performance from low-level GPU kernels to large-scale distributed systems. Use modern LLMs and agent-based tooling where it accelerates development and tuning of the ROCm ecosystem.
  • Accelerate foundation models and agents: Improve training, post-training, and inference for LLMs and autonomous AI workloads so AMD is the default platform for the most demanding use cases.
  • Co-design hardware and software: Partner on the full lifecycle-from GPU architecture input to software for new accelerators-and engage with the broader AI community to keep AMD at the forefront.

WHAT WE'RE LOOKING FOR
We need someone who can go deep in the areas below and collaborate effectively.
SYSTEMS & GPU PERFORMANCE (KERNEL ENGINEERING)
  • Expert-level modern C++ and design of large, performance-critical systems.
  • Strong grasp of GPU architecture, memory hierarchy, and kernel optimization (HIP/CUDA).
  • Hands-on delivery on large-scale C++/HIP/CUDA codebases, such as ROCm (rocBLAS, hipDNN, Composable Kernel, AITemplate), the CUDA ecosystem (cuBLAS, cuDNN, CUTLASS, Thrust, CUB, NCCL), and ML framework cores such as PyTorch, TensorFlow, or JAX (C++/HIP/CUDA paths).
  • Comfort diagnosing bottlenecks with profilers (for example, ROCm Profiler and Nsight) in multi-GPU, distributed settings.

AI POST-TRAINING & LLM SYSTEMS
  • Deep understanding of transformers, attention, and the full model lifecycle.
  • Hands-on work in alignment and post-training-for example, SFT, RLHF, and GRPO.
  • Awareness of current LLM trends, including MoE, quantization, speculative decoding, and agentic systems.
  • Experience optimizing post-training and inference pipelines at scale.

PREFERRED BACKGROUND
  • Substantial professional experience in software development within performance-critical environments.
  • Extensive HIP/CUDA experience optimizing deep learning and OSS LLM inference/training kernels and operators.
  • Strong technical ownership and a track record of shipping complex systems.
  • Clear communication and influence across teams.
  • Plus: Deep familiarity with the AMD ROCm/HIP ecosystem.
  • Plus: Working knowledge of RTL design and Verilog/SystemVerilog for hardware-software co-design.

EDUCATION
  • Bachelor's in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
  • Master's preferred; PhD a plus.
  • Publications in AI/ML, GPU computing, or systems optimization are valued.

#LI-AG2
#LI-HYBRID
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
This posting is for an existing vacancy.

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