RDMA Engineer - Supercomputing
xAI
RDMA Engineer - Supercomputing
Job Description
About xAI
xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Role
RDMA Engineers on xAI’s Supercomputing team design and optimize low-latency, high-bandwidth networking solutions using NVIDIA’s RDMA-capable technologies to support some of the world’s largest GPU supercomputing clusters. These clusters drive AI training and inference workloads, demanding cutting-edge performance and scalability.
Focus
- Develop and tune RDMA-based communication systems leveraging NVIDIA GPUs and Mellanox NICs (InfiniBand, RoCE) for ultra-fast data transfer between nodes.
- Implement and optimize GPUDirect RDMA to enable direct memory access between GPUs and network interfaces, minimizing CPU overhead.
- Integrate RDMA solutions with Kubernetes-based workloads, ensuring seamless operation across distributed compute and storage systems.
- Collaborate with AI researchers and infrastructure teams to accelerate data pipelines and collective communications using NCCL and MPI.
- Troubleshoot and resolve performance bottlenecks in high-throughput, low-latency networking environments.
Ideal Experience
- Hands-on experience with NVIDIA RDMA technologies (e.g., GPUDirect RDMA, RoCE, InfiniBand) in HPC or AI supercomputing environments.
- Proficiency in programming with Rust, C, or C++ for low-level networking and system optimization.
- Familiarity with NVIDIA’s networking stack, including Mellanox drivers, libraries (e.g., libibverbs), and tools (e.g., NVPeerMemory).
- Experience optimizing distributed systems with MPI, NCCL, or similar frameworks for GPU-accelerated workloads.
- Knowledge of Kubernetes networking and integrating RDMA into containerized environments.
- Bonus: Background in AI/ML training workflows and their networking demands (e.g., large-scale parameter synchronization).
Tech Stack
- NVIDIA GPUs and Mellanox networking (InfiniBand, RoCE)
- RDMA protocols (e.g., GPUDirect RDMA, RoCEv2)
- Kubernetes
- Rust and C/C++
- MPI (Message Passing Interface) and NCCL (NVIDIA Collective Communications Library)
Annual Salary Range
$180,000 - $440,000 USD
Benefits
Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
Locations
- Palo Alto, CA,
- San Francisco, CA,
Salary
180,000 - 440,000 USD / yearly
Skills Required
- NVIDIA RDMA technologies (GPUDirect RDMA, RoCE, InfiniBand)intermediate
- Rust, C, C++intermediate
- NVIDIA networking stack (Mellanox drivers, libibverbs, NVPeerMemory)intermediate
- MPI, NCCLintermediate
- Kubernetes networkingintermediate
- HPC or AI supercomputingintermediate
- Distributed systems optimizationintermediate
- Low-level networking and system optimizationintermediate
Required Qualifications
- Hands-on experience with NVIDIA RDMA technologies (e.g., GPUDirect RDMA, RoCE, InfiniBand) in HPC or AI supercomputing environments (experience)
- Proficiency in programming with Rust, C, or C++ for low-level networking and system optimization (experience)
- Familiarity with NVIDIA’s networking stack, including Mellanox drivers, libraries (e.g., libibverbs), and tools (e.g., NVPeerMemory) (experience)
- Experience optimizing distributed systems with MPI, NCCL, or similar frameworks for GPU-accelerated workloads (experience)
- Knowledge of Kubernetes networking and integrating RDMA into containerized environments (experience)
Preferred Qualifications
- Background in AI/ML training workflows and their networking demands (e.g., large-scale parameter synchronization) (experience)
Responsibilities
- Develop and tune RDMA-based communication systems leveraging NVIDIA GPUs and Mellanox NICs (InfiniBand, RoCE) for ultra-fast data transfer between nodes
- Implement and optimize GPUDirect RDMA to enable direct memory access between GPUs and network interfaces, minimizing CPU overhead
- Integrate RDMA solutions with Kubernetes-based workloads, ensuring seamless operation across distributed compute and storage systems
- Collaborate with AI researchers and infrastructure teams to accelerate data pipelines and collective communications using NCCL and MPI
- Troubleshoot and resolve performance bottlenecks in high-throughput, low-latency networking environments
Benefits
- general: Equity
- general: Comprehensive medical, vision, and dental coverage
- general: Access to a 401(k) retirement plan
- general: Short & long-term disability insurance
- general: Life insurance
- general: Various other discounts and perks
Tags & Categories
Answer 10 quick questions to check your fit for RDMA Engineer - Supercomputing @ xAI.
RDMA Engineer - Supercomputing
xAI
RDMA Engineer - Supercomputing
Job Description
About xAI
xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Role
RDMA Engineers on xAI’s Supercomputing team design and optimize low-latency, high-bandwidth networking solutions using NVIDIA’s RDMA-capable technologies to support some of the world’s largest GPU supercomputing clusters. These clusters drive AI training and inference workloads, demanding cutting-edge performance and scalability.
Focus
- Develop and tune RDMA-based communication systems leveraging NVIDIA GPUs and Mellanox NICs (InfiniBand, RoCE) for ultra-fast data transfer between nodes.
- Implement and optimize GPUDirect RDMA to enable direct memory access between GPUs and network interfaces, minimizing CPU overhead.
- Integrate RDMA solutions with Kubernetes-based workloads, ensuring seamless operation across distributed compute and storage systems.
- Collaborate with AI researchers and infrastructure teams to accelerate data pipelines and collective communications using NCCL and MPI.
- Troubleshoot and resolve performance bottlenecks in high-throughput, low-latency networking environments.
Ideal Experience
- Hands-on experience with NVIDIA RDMA technologies (e.g., GPUDirect RDMA, RoCE, InfiniBand) in HPC or AI supercomputing environments.
- Proficiency in programming with Rust, C, or C++ for low-level networking and system optimization.
- Familiarity with NVIDIA’s networking stack, including Mellanox drivers, libraries (e.g., libibverbs), and tools (e.g., NVPeerMemory).
- Experience optimizing distributed systems with MPI, NCCL, or similar frameworks for GPU-accelerated workloads.
- Knowledge of Kubernetes networking and integrating RDMA into containerized environments.
- Bonus: Background in AI/ML training workflows and their networking demands (e.g., large-scale parameter synchronization).
Tech Stack
- NVIDIA GPUs and Mellanox networking (InfiniBand, RoCE)
- RDMA protocols (e.g., GPUDirect RDMA, RoCEv2)
- Kubernetes
- Rust and C/C++
- MPI (Message Passing Interface) and NCCL (NVIDIA Collective Communications Library)
Annual Salary Range
$180,000 - $440,000 USD
Benefits
Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
Locations
- Palo Alto, CA,
- San Francisco, CA,
Salary
180,000 - 440,000 USD / yearly
Skills Required
- NVIDIA RDMA technologies (GPUDirect RDMA, RoCE, InfiniBand)intermediate
- Rust, C, C++intermediate
- NVIDIA networking stack (Mellanox drivers, libibverbs, NVPeerMemory)intermediate
- MPI, NCCLintermediate
- Kubernetes networkingintermediate
- HPC or AI supercomputingintermediate
- Distributed systems optimizationintermediate
- Low-level networking and system optimizationintermediate
Required Qualifications
- Hands-on experience with NVIDIA RDMA technologies (e.g., GPUDirect RDMA, RoCE, InfiniBand) in HPC or AI supercomputing environments (experience)
- Proficiency in programming with Rust, C, or C++ for low-level networking and system optimization (experience)
- Familiarity with NVIDIA’s networking stack, including Mellanox drivers, libraries (e.g., libibverbs), and tools (e.g., NVPeerMemory) (experience)
- Experience optimizing distributed systems with MPI, NCCL, or similar frameworks for GPU-accelerated workloads (experience)
- Knowledge of Kubernetes networking and integrating RDMA into containerized environments (experience)
Preferred Qualifications
- Background in AI/ML training workflows and their networking demands (e.g., large-scale parameter synchronization) (experience)
Responsibilities
- Develop and tune RDMA-based communication systems leveraging NVIDIA GPUs and Mellanox NICs (InfiniBand, RoCE) for ultra-fast data transfer between nodes
- Implement and optimize GPUDirect RDMA to enable direct memory access between GPUs and network interfaces, minimizing CPU overhead
- Integrate RDMA solutions with Kubernetes-based workloads, ensuring seamless operation across distributed compute and storage systems
- Collaborate with AI researchers and infrastructure teams to accelerate data pipelines and collective communications using NCCL and MPI
- Troubleshoot and resolve performance bottlenecks in high-throughput, low-latency networking environments
Benefits
- general: Equity
- general: Comprehensive medical, vision, and dental coverage
- general: Access to a 401(k) retirement plan
- general: Short & long-term disability insurance
- general: Life insurance
- general: Various other discounts and perks
Tags & Categories
Answer 10 quick questions to check your fit for RDMA Engineer - Supercomputing @ xAI.