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Rdma Gpu Jobs (NOW HIRING)

Fuse Energy

Founding GPU Engineer

Familiarity with multi-GPU/multi-node scaling (NCCL, MPI, RDMA/InfiniBand) * Strong grasp of memory optimisation, kernel fusion and parallel algorithm design * Comfortable working across the stack ...

Webhosting

$90 - $130/hr

Network DevOps Engineer, RDMA Fabric Automation - Multiple Openings Remote Full-time Not specified ... Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity ...

Talanto

$100 - $150/hr

Optimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking. * Implement custom operators and fused kernels in PyTorch, JAX, or Triton. * Collaborate with ML ...

New

CoreWeave

Senior Engineer, Storage

New York, NY · On-site

$153K - $204K/yr

Work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency. * Lead efforts to improve the ...

Vultr

Strategic Technical Account Manager GPU

$115K - $140K/yr

Advise on cluster design: multi-GPU topology, NVLink/NVSwitch considerations, RDMA, Infiniband and RoCE Ethernet, networking throughput, and storage IOPS requirements. * Guide customers in selecting ...

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Rdma Gpu information

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$42.5K

$123.8K

$175K

How much do rdma gpu jobs pay per year?

As of Sep 6, 2026, the average yearly pay for rdma gpu in the United States is $123,786.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $142,500.00 per year, depending on experience, location, and employer.

What is an RDMA GPU?

RDMA GPUs are graphics processing units that support Remote Direct Memory Access (RDMA) technology, enabling direct memory transfers between the GPU and remote devices or other GPUs across a network without involving the host CPU. This technology is commonly used in high-performance computing, AI, and data centers to reduce latency and increase data throughput. RDMA GPUs allow faster data exchange for distributed computing tasks, such as large-scale machine learning training, by bypassing traditional network bottlenecks.

How does an RDMA GPU engineer typically collaborate with software and hardware teams to optimize performance?

As an RDMA GPU engineer, you’ll regularly work alongside both software developers and hardware architects to ensure that high-speed data transfers between GPUs and other components are efficient and reliable. This collaboration often involves troubleshooting bottlenecks, tuning drivers, and optimizing memory access patterns. You may also participate in code reviews, joint debugging sessions, and performance benchmarking to align system-level improvements. Effective communication across multidisciplinary teams is essential to deliver best-in-class solutions for demanding workloads like machine learning or scientific computing.

What are the key skills and qualifications needed to thrive as an RDMA GPU engineer, and why are they important?

To thrive as an RDMA GPU Engineer, you need a solid background in computer science or engineering, with expertise in GPU architectures, networking protocols, and RDMA (Remote Direct Memory Access) technologies. Familiarity with CUDA, InfiniBand, RoCE, and relevant profiling or debugging tools is typically required. Strong problem-solving, teamwork, and communication skills help in collaborating effectively on complex, performance-critical systems. These skills are crucial for optimizing high-performance computing applications and ensuring efficient data transfer between GPUs and networked devices.

What is the difference between Rdma Gpu vs Network Engineer?

AspectRdma GpuNetwork Engineer
Required CredentialsComputer science or related degree, certifications in GPU computing or high-performance networkingNetworking certifications (CCNA, CCNP), degree in computer science or related field
Work EnvironmentData centers, high-performance computing labs, research facilitiesCorporate offices, data centers, telecommunication environments
Industry UsageAI, machine learning, scientific computing, data analyticsIT infrastructure, network design, security, and maintenance

Rdma Gpu specialists focus on optimizing GPU performance and high-speed data transfer using RDMA technology, primarily in computing and research environments. Network Engineers design, implement, and maintain network systems. While both roles involve high-tech infrastructure, Rdma Gpu roles are more specialized in GPU and high-performance data transfer, whereas Network Engineers focus on network connectivity and security.

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Rdma Gpu jobs near you
Infographic showing various Rdma Gpu job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 97% Full Time, and 2% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $123,786 per year, or $59.5 per hour.

Performance/ Benchmark Engineer - NVIDIA GPU Systems

Yoh - A Day & Zimmerman Company

Santa Clara, CA • On-site

$300K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 22 days ago

Key responsibilities

  • Develop and execute performance benchmarks for AI inference and machine learning workloads across NVIDIA GPU systems.

  • Characterize performance on platforms including NVIDIA DGX and B200/B300-based systems, analyzing throughput, latency, utilization, memory behavior, and scaling efficiency.

  • Build benchmarking methodologies, automation, and reporting frameworks to produce repeatable performance results.

Job description

Performance/ Benchmark Engineer - NVIDIA GPU Systems
NVIDIA GPU Systems / AI Inference / Performance Engineering
Overview
Seeking a hands-on Performance and Benchmarking Engineer to characterize and optimize AI workloads running on large-scale NVIDIA GPU infrastructure. This role sits within an architecture team and focuses primarily on GPU compute performance, AI inference, and system-level benchmarking, with networking performance as a secondary consideration.
Key Responsibilities
  • Develop and execute performance benchmarks for AI inference and machine learning workloads across NVIDIA GPU systems.
  • Characterize performance on platforms including NVIDIA DGX and B200/B300-based systems, analyzing throughput, latency, utilization, memory behavior, and scaling efficiency.
  • Evaluate AI models and workload configurations to identify performance bottlenecks and recommend system or architecture improvements.
  • Build benchmarking methodologies, automation, and reporting frameworks to produce repeatable performance results.
  • Collaborate with architecture, compute, networking, and software teams to optimize end-to-end AI cluster performance.
Required Qualifications
  • Deep hands-on experience with NVIDIA GPU compute platforms and AI/ML performance benchmarking.
  • Strong understanding of AI inference, model performance, workload characterization, and GPU architecture.
  • Experience with NVIDIA DGX, B200/B300, H100/H200, Blackwell, Hopper, or comparable GPU systems.
  • Experience analyzing performance metrics including latency, throughput, GPU utilization, memory bandwidth, and multi-GPU scaling.
  • Strong scripting and automation skills using Python or similar languages.
Preferred Qualifications
  • Experience with MLPerf, CUDA, NCCL, TensorRT, Triton Inference Server, PyTorch, Nsight, or similar AI performance and profiling technologies.
  • Experience benchmarking LLMs, inference workloads, distributed training, or large-scale GPU clusters.
  • Familiarity with RDMA, RoCE, InfiniBand, Ethernet, GPUDirect RDMA, or networking considerations affecting GPU cluster performance.

Estimated Min Rate: $250,000.00/Annually
Estimated Max Rate: $300,000.00/Annually
What s In It for You?
We welcome you to be a part of the largest and legendary global staffing companies to meet your career aspirations. Yoh s network of client companies has been employing professionals like you for over 65 years in the U.S., UK and Canada. Join Yoh s extensive talent community that will provide you with access to Yoh s vast network of opportunities and gain access to this exclusive opportunity available to you. Benefit eligibility is in accordance with applicable laws and client requirements. Benefits include:
  • Medical, Prescription, Dental & Vision Benefits (for employees working 20+ hours per week)
  • Health Savings Account (HSA) (for employees working 20+ hours per week)
  • Life & Disability Insurance (for employees working 20+ hours per week)
  • MetLife Voluntary Benefits
  • Employee Assistance Program (EAP)
  • 401K Retirement Savings Plan
  • Direct Deposit & weekly epayroll
  • Referral Bonus Programs
  • Certification and training opportunities

Note: Any pay ranges displayed are estimations. Actual pay is determined by an applicant's experience, technical expertise, and other qualifications as listed in the job description. All qualified applicants are welcome to apply.
Yoh, a Day & Zimmermann company, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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