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Rdma Gpu Jobs (NOW HIRING)

CoreWeave

Sr. Engineer, Storage

... 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 reliability, durability ...

CoreWeave

Staff Engineer, Storage Engine

... 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 reliability, durability ...

Nvidia

Senior GPU System Architect

Santa Clara, CA · Hybrid

Collaborate with other teams to architect RDMA-capable hardware and define transport layer optimizations for GPU-based large scale AI workload deployments. * Use and modify system models, perform ...

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

... RDMA/InfiniBand optimization experience • Contributions to GPU libraries or frameworks • Low-level debugging skills (PTX/SASS reading) Company : Genmo is an artificial intelligence creative ...

BitDeer

Senior GPU Systems & Fabric Engineer

Austin, TX · On-site +1

$180K - $320K/yr

Configure and optimize high-performance host networking stacks, including RDMA, SR-IOV, RoCEv2, and ... Implement and manage sophisticated GPU slicing technologies (MIG, vGPU) to enable efficient multi ...

Bitdeer

$180 - $240/hr

Configure and optimize high-performance host networking stacks, including RDMA, SR-IOV, RoCEv2, and ... Implement and manage sophisticated GPU slicing technologies (MIG, vGPU) to enable efficient multi ...

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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 Aug 27, 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 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 79% Physical, 7% Hybrid, and 14% Remote job distribution, with an average salary of $123,786 per year, or $59.5 per hour.

Lab Administrator

DDN Storage

Columbia, MD • On-site

Other

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

Technical/Research Lab Environment Manager

Responsible for the setup, maintenance, security, and day-to-day operation of a technical/research lab environment (servers, storage systems, networking equipment, and lab-issued workstations), ensuring high availability, performance, and compliance with organizational policies.

Key Responsibilities
  • Install, configure, and maintain lab hardware (servers, storage arrays, NICs, switches) and software (OS images, drivers, monitoring tools)
  • Manage user access, accounts, and permissions across lab systems
  • Monitor system health, performance, and capacity (CPU, memory, storage, network utilization)
  • Troubleshoot hardware/software issues and coordinate with vendors for support/RMAs
  • Maintain documentation: network diagrams, asset inventories, configuration baselines, SOPs
  • Implement and enforce security policies (patching, firewall rules, access controls)
  • Manage backups, disaster recovery procedures, and data retention policies
  • Support researchers/engineers with environment setup for experiments, benchmarks, or testing (e.g., provisioning compute nodes, storage volumes, network configs)
  • Track licensing, warranties, and hardware lifecycle (procurement to decommissioning)
  • Coordinate lab scheduling/resource allocation if shared across teams
Required Skills/Qualifications
  • Strong Linux administration experience (Ubuntu/RHEL/CentOS)
  • Networking fundamentals (TCP/IP, VLANs, bonding/LACP, basic troubleshooting)
  • Experience with storage systems (SAN/NAS, parallel filesystems like Lustre/GPFS a plus)
  • Scripting ability (Bash, Python) for automation
  • Familiarity with virtualization/containerization (KVM, Docker) is a plus
  • Experience with monitoring tools (Prometheus/Grafana, Nagios, Zabbix)
  • Understanding of hardware components (CPUs, NUMA architecture, PCIe, NICs/RDMA)
  • Good documentation and communication skills
Nice to Have
  • Experience with HPC/AI infrastructure (InfiniBand, RDMA, GPU clusters)
  • Experience with configuration management (Ansible, Puppet)

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