We are looking for a Senior networking test engineer with strong system‑level debugging skills to join our End‑to‑End Verification team. You will work on cutting‑edge Ethernet‑based AI clusters, owning complex issues across hardware, system software and AI workloads. We are widely considered to be one of the technology worlds most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

What youll be doing:

Design and review test and product requirements across the Ethernet / NIC / DPU / Switch portfolio, focusing on large‑scale AI cluster behavior.

Build and maintain realistic customer‑like testbeds, including heterogeneous hardware, OS / driver combinations and complex network fabrics.

Own end‑to‑end cluster troubleshooting: reproduce customer scenarios, triage across the stack and drive issues to root cause and fix.

Read and understand relevant source code to identify defects, validate fixes and improve logging and instrumentation.

Collaborate closely with development teams to debug NCCL, RoCE/RDMA and related networking components using logs, code inspection and targeted experiments.

Define tests and guide the automation team to implement robust suites that produce actionable logs, metrics and traces.

Run Regression, Performance, Functional and Scale testing, analyze results and provide clear, data‑driven reports to stakeholders.

Profile and benchmark deep learning training and inference workloads, correlating model‑level metrics with system and network telemetry to uncover bottlenecks.

We are looking for an AI Test Architect joining E2E Verification group to profile Innovative large scale Distributed training on our AI End-to-End solutions in a large scale supercomputing clusters. Provide insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest Accelerated Computing and Deep Learning software and hardware platforms, with researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, Switch, HCA, CPU and GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.

What youll be doing:

Profiling, benchmarking, and analyzing deep learning models to identify areas for optimization and improvement in terms of performance, efficiency, and accuracy, with a strong emphasis on networking aspects.

Collaborating closely with data scientists, researchers, development, automation teams to design and implement scalable training pipelines and frameworks that demonstrate large scale high -performance networking capabilities.

Staying up-to-date with the latest advancements in deep learning algorithms, architectures, our GPU technologies, and high-performance networking solutions.

Optimizing deep learning models for performance, memory usage, and power efficiency while maximizing high-performance networking features on our supercomputers.

Providing insights and recommendations based on the analysis of large-scale training results, specifically focusing on networking bottlenecks and optimizations, to improve model outcomes and achieve business objectives.

Collaborating with hardware engineers to guide the development and integration of efficient networking solutions for deep learning, including exploring network architecture optimizations and bringing to bear technologies such as RDMA or InfiniBand.

We are looking for an AI Test Architect joining E2E Verification group to profile Innovative large scale Distributed training on NVIDIA AI End-to-End solutions in a large scale supercomputing clusters. Provide insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest Accelerated Computing and Deep Learning software and hardware platforms, with researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, Switch, HCA, CPU and GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.

What youll be doing:

Profiling, benchmarking, and analyzing deep learning models to identify areas for optimization and improvement in terms of performance, efficiency, and accuracy, with a strong emphasis on networking aspects.

Collaborating closely with data scientists, researchers, development, automation teams to design and implement scalable training pipelines and frameworks that demonstrate large scale high -performance networking capabilities.

Staying up-to-date with the latest advancements in deep learning algorithms, architectures, NVIDIA GPU technologies, and high-performance networking solutions.

Optimizing deep learning models for performance, memory usage, and power efficiency while maximizing high-performance networking features on NVIDIA supercomputers.

Providing insights and recommendations based on the analysis of large-scale training results, specifically focusing on networking bottlenecks and optimizations, to improve model outcomes and achieve business objectives.

Collaborating with hardware engineers to guide the development and integration of efficient networking solutions for deep learning, including exploring network architecture optimizations and bringing to bear technologies such as RDMA or InfiniBand.

The Networking Advanced Development Software team develops new groundbreaking technologies to enable new market shares for the company and tighten customer relationships. These are emerging technologies in networking and distributed computing for the booming AI factories and data centers. They span areas such as AI neural networks, Deep Learning, High Performance Computing (HPC), Storage, Cloud, SW Defined Network, Network Function Virtualization and more. We develop the solutions top-down, all the way from application behavioral analysis, to architecture definition and down to the implementation, using the world-leading our devices. The development traverses any needed component - application SW, middleware SW, OS kernel subsystems, device drivers, embedded SW (Firmware) and CUDA GPU. We collaborate with partners and key customers in the analysis processes and engage with open source communities introducing our leading features.

What youll be doing:

Design and implement solutions throughout all layers from high level application, OS and driver subsystem to firmware.

Work on impactful projects involving state-of-the-art high-performance computing hardware and software.

Provide insight and technical guidance and collaborate with peers from across the company - including software architecture, chip architecture, and engineering departments to improve our future technology.

Collaborate with our partners and customers.

We are looking for a 100% hands-on Storage Services Software engineer to join the block storage group. You will be a member of a team that builds the next generation block storage capabilities. You will work closely with a variety of teams and architects including the networking team, and external customers. You will take part in defining the software architecture and implementation of the most advanced storage services! Services that will need to meet extreme performance and scalability demands! We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform of tomorrow.

What youll be doing:

100% hands-on coding role in C language, kernel and userspace.

Research, design, implement and test, new and existing, networking features for distributed storage services and features of our block storage solution, in both Host and DPU environments.

Acquire understanding of the algorithms, the technicalities and the interaction with other components across our block storage ecosystem.

Analyze and solve challenging bugs and customer cases in large scale production systems, identifying issues in our or inbox kernel modules and often in other components. Drive new solutions based on any issues that arise.

We are looking for a skilled Software Developer with strong hardware knowledge to join our diverse team passionate about developing low-level software and test infrastructure for our networking and Interconnect products. As a technical focal point, you will work at the intersection of hardware and software, taking ownership of driver development, hardware bring-up, and test system architecture. You will be instrumental in driving innovation by developing low-level software that directly controls hardware, debugging sophisticated hardware-software interactions, and creating robust testing solutions. If you're passionate about code development, automation, innovation, reading schematics, debugging hardware with software tools, and becoming a key technical contributor, we'd love to have you on board!


What You'll Be Doing:

Collaborate with multi-functional teams including hardware, electrical, thermal, and mechanical engineers to understand hardware specifications and develop corresponding test requirements.

Take the lead in debugging hardware-software integration issues using instruments, and software tools to pinpoint root causes.

Develop low-level drivers in C/C++ for hardware components and build DLL wrappers for integration with higher-level C# applications.

Review and interpret hardware schematics and datasheets to understand signal flows, timing requirements, and implement appropriate software control mechanisms.

Lead all aspects of hardware bring-up, validation, and deployment of test solutions to production environments, ensuring accurate integration.

We are looking for an engineer with the ability to thrive in an environment with complex software and hardware designs, who can take ownership, and lead the development of key SW components for Amazon network cards.

You will take part in developing, integrating, and deploying advanced networking technologies, starting from the identification and definition of project requirements, feature development, deployment and operational support, on a very large scale.

As part of your role you will join a team of engineers who are developing software implementing our RDMA technology, for Machine Learning and High Performance Computing (HPC) customers.

Your code will run on millions of servers worldwide, as part of the Nitro system. Not many software engineers in the world have the opportunity to create code that runs at such a large scale.
The role includes working closely with HW, FW, and SW teams all over the world.

We seek a highly motivated Network Performance Exploration Engineer to join our team of experts and help shape the foundational infrastructure for the AI revolution. Our next-generation networking systems are at the forefront of connecting and powering the world's most advanced AI clusters. As a key member of our architecture team, you will be responsible for exploring and identifying critical network optimization opportunities across our entire hardware and software stack, analyzing how system-level changes impact application-level performance.

What Youll Be Doing:

Explore and validate end-to-end application performance, defining comprehensive test plans and critical metrics to identify optimization opportunities in both hardware and software.

Establish and maintain a comprehensive database of benchmark results, tracking performance across releases to drive data-informed decisions.

Conduct deep-dive analysis into communication libraries (like NCCL), system software, and hardware configurations to investigate performance characteristics, validate architectural theories, and identify bottlenecks.

Provide critical performance data to correlate and enhance simulation tools, ensuring our models accurately predict real-world hardware behavior.

Analyze application-level traffic patterns (e.g., LLMs) on our advanced networking fabrics to identify hardware and software optimization opportunities and tune system parameters.

Lead Proof-of-Concept (POC) projects to prototype and evaluate potential hardware and software optimizations and their impact on application performance.

We are looking for an enthusiastic software engineer to join our AI networking acceleration team, to work on a groundbreaking open-source library, using hardware offloads, GPU Kernels and RDMA network cards. Our product is a performance-oriented low-level infrastructure, crafted to change the way inference works.

We thrive as a team in a deeply strong environment, and we're passionate about innovation. The rewards are sweet and include working with some of the brightest people in the industry, an aggressive compensation plan that rewards top performers, and the opportunity to collaborate on products that transform daily the way people work and play.

What you'll be doing:
Developing a highly optimized inference framework
Running on the worlds largest supercomputers and data centers.
The work environment is dynamic and challenging as our employees work on innovative, next-generation products at the forefront of technology in terms of performance, scalability, and features.

We are seeking a highly motivated High-Performance System Architect to join our team of experts and help shape the future of high-performance and ML / AI computing. Our next-generation NVL systems will be at the forefront of connecting and powering the world's most advanced compute clusters, which would be used to train the most advanced AI models such as GPT and DeepSeek. As a high-performance system architect, you will have the opportunity to work on some of the most cutting-edge technology and help to drive the innovation of our next generation networks that will be used by top researchers and engineers around the world.

What youll be doing:
Define the NVL system architecture end-to-end, by internal requirements and customers requirements through all product life cycles (post/pre silicon, on deployments).
Research various of solutions to enable the next large-scale-high-performance computing clusters. The position spans over various layers from algorithms, software, firmware, and HW.
Collaborate with cross-functional teams, including other architecture teams, logic design, system software, firmware, and research teams, to ensure the successful execution of the project.