דרושים » תוכנה » Senior Software Advanced Developer

We are seeking a highly skilled Senior Performance Engineer to join our Performance and R&D organizations. In this role, you will help build and evolve systems that support performance analysis, telemetry, and optimization for large-scale GPU- and CPU-based clusters used in AI and high-performance computing environments. You will work closely with hardware, networking, firmware, and software teams to collect, analyze, and interpret performance data from live systems. This is a fast-paced R&D environment where system behavior and requirements evolve rapidly, requiring adaptable engineering solutions and strong analytical thinking.

What youll be doing:

Profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters.

Explore performance characteristics of high-performance networking and collective communications (e.g., NCCL, RDMA, MPI, RoCE).

Identify performance bottlenecks across networking, compute, memory, and system architecture.

Develop and enhance performance analysis, benchmarking, and diagnostic tools.

Define performance test plans and establish expectations for new technologies and platforms.

Collaborate across hardware, firmware, networking, systems, and software teams to provide actionable performance insights.

Support telemetry collection and data refinement efforts to enable accurate performance analysis.

Maintain high standards for data quality, reproducibility, and traceability of performance results.

We are seeking an AI Networking Architect to join the Networking Research Group. This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them. In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.

You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your insights will directly shape our products across the full stack - from applications and software libraries to hardware architecture and physical design.

What Youll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.

Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.

Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.

Partner with architecture, software, and product teams to influence our future networking and AI infrastructure roadmaps.

Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.

We are looking for a Distinguished Engineer to help shape the future of AI infrastructure. As part of our advanced development and research efforts, you will drive technical vision and innovation across the AI software stack, spanning GPU computing, RDMA, NVLink, storage, and large-scale distributed systems. You will research next-generation system designs, influence product and platform direction, and help define how massive-scale AI environments are built, optimized, and operated through hardware-software co-design.

What youll be doing:

Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and large-scale distributed infrastructure.

Lead deep technical investigations and proof-of-concept development in areas related to distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design.

Work closely with multiple teams across us to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions.

Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage layers to improve performance, scalability, and efficiency.

Guide the design of environments that support massive-scale AI training and inference workloads in production.

We are seeking an exceptional Network Engineer to join the Vertical Verification Group. As a senior engineer, you will contribute to the Vertical Verification work, concentrating on validating and improving complex Ethernet and InfiniBand systems within our Data Center and HPC environments.

You will play a key role in testing advanced networking features, building complex customer-like topologies, and ensuring our products meet industry-leading benchmarks of performance, efficiency, and quality. You will collaborate closely with architects, software engineers, and hardware teams across NIC, HCA, switches, CPUs, and GPUs in a fast-paced and highly technical environment. This is an outstanding opportunity to join a highly skilled team and contribute significantly to groundbreaking technology!

What youll be doing:
Review architecture, build, and requirements for new networking features across Ethernet and InfiniBand portfolios.
Compose and build complex testbed topologies that emulate customer environments.
Implement, run and optimize integration test plans including functional, regression, and performance testing.
Identify, reproduce, and debug issues; work closely with R&D to drive root cause analysis and resolution.
Collaborate with automation teams.
Analyze and optimize network performance, latency, and efficiency.
Provide clear status updates, reports, and insights on system quality and performance.

We are looking for a Host and Systems Performance Manager to join ur Networking Performance team!

In this role, you will lead a team of engineers who measure, analyze, and improve NIC, host, DOCA networking stack, and system-level performance across our networking products and platforms. We work across the full product lifecycle, from early architecture and pre-silicon modeling through post-silicon bring-up, validation, characterization, and GA readiness.

We are looking for someone who enjoys building teams, turning complex performance data into clear direction, and partnering across engineering groups to improve products that support AI, HPC, cloud, and accelerated networking workloads.

What Youll Be Doing:
Lead, coach, and develop a team focused on NIC, host, DOCA networking stack, and system-level performance. You will define performance test plans, methodologies, metrics, and success criteria for our new networking technologies.
Guide pre-silicon and post-silicon performance planning, analysis, reporting, and readiness reviews. Your team will benchmark and profile workloads across RDMA, RoCE, InfiniBand, Ethernet, MPI, NCCL, DOCA, storage, security, and host networking stacks.
Identify bottlenecks across NIC, DPU, CPU, memory, PCIe, firmware, drivers, Linux networking, DOCA, and full-system architecture. We will look to you to lead root-cause analysis, coordinate mitigation plans, and help hardware, firmware, software, architecture, validation, and product teams align on performance goals.

Our Network Architecture, Modeling and Performance Insights group is seeking a skilled and driven hands-on Network Modeling Architect to conduct advanced network research and optimization while utilizing and enhancing our advanced simulation tools.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network topologies, configurations, logic and traffic patterns, and analyzing their effect on end-to-end performance. You will develop expertise in our simulation tools and write code daily to contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance. If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

 

What you'll be doing:

Analyze and model our AI and High Performance Computing offerings, deep dive into network behavior for training and inference and generate insights to directly impact the architecture of next-generation of AI systems. Conduct advanced network modeling, research and optimization using innovative simulation tools.

Write production-quality C++ and Python code daily. Hands-on modeling of advanced network topologies, configurations and traffic patterns representing real life AI workloads, and analyze their effect on the system's performance. Actively develop the simulator software solution while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.

We are looking for a Senior Software Engineer to join our team developing the core technologies behind our SmartNIC platform. Your work will directly impact next-generation AI infrastructure, cloud networking, and high-performance data centers used by customers around the world.

What you'll be doing:

Architect, design, and develop next-generation networking acceleration technologies.

Build and enhance core software components within the DOCA SDK.

Work closely with architects, customers, and engineering teams to understand requirements and deliver scalable, high-performance solutions.

Collaborate across the software stack, including applications, virtualization, drivers, Linux kernel, firmware, and hardware teams.

Drive technical decisions and contribute to the design of performant, maintainable software.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network topologies, configurations, logic and traffic patterns, and analyzing their effect on end to end performance. You will develop expertise in our simulation tools and contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance.

If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

What you'll be doing:

Analyze and model our AI and High Performance Computing offerings, deep dive into network behavior for training and inference and generate insights to directly impact the architecture of next-generations of AI systems. Conduct advanced network modeling, research and optimization using innovative simulation tools.

Implement modeling of advanced network topologies, configurations and traffic patterns which represent real life AI workloads, and analyze their effect on the systems performance. Actively develop the simulator software solution while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.

We are looking for an excellent Drivers Team leader to lead the Inbox Linux Drivers team and make a wide impact on the company products and teams worldwide. The role includes leading the development and maintenance of cutting-edge Linux kernel drivers and userspace libraries for our networking technologies, while managing a team of highly skilled Linux engineers responsible for delivering production-quality software across multiple products and distributions.

What youll be doing:

Lead a team of Linux kernel engineers responsible for developing, maintaining, and delivering Linux networking drivers for our NICs across multiple product lines, including Inbox drivers, our Kernel, and DOCA Host.

Drive the design, implementation, maintenance, and integration of Linux kernel drivers and accompanying userspace libraries for state-of-the-art Ethernet and RDMA networking technologies.

Own the teams technical execution, roadmap, prioritization, and delivery while mentoring engineers and fostering technical excellence.

Collaborate closely with architecture, firmware, hardware, validation, DevOps, product, and customer-facing teams across the globe to deliver robust and scalable networking solutions.

Lead complex debugging and performance investigations across the Linux networking stack, working with both internal stakeholders and open-source communities.

Ensure high software quality through strong engineering practices, code reviews, automation, and continuous integration.

Be part of an experienced organization with a collaborative culture, solving challenging problems that power next-generation AI, cloud, and high-performance computing infrastructure.

We seek a versatile Senior Software Engineer who is passionate about performance optimization and generative AI. Our team brings the latest research in LLM inference - from novel decoding strategies to quantization schemes - into production across our hardware lineup, from large data center servers to powerful edge devices. We work on the most advanced architectures in the field, with a focus on NVIDIA's own.

What you'll be doing:

Implement and optimize inference algorithms for LLM and omnimodal architectures, including hybrid Mamba-Transformer and mixture-of-experts models.

Profile inference pipelines using NVIDIA's profiling and simulation tools. Correlate simulation predictions against real hardware across data center and edge devices.

Write and tune GPU kernels (CUDA, Triton) for operators like fused MoE layers, SSM state updates, and quantized GEMMs.

Solve distributed inference problems: expert parallelism, communication-compute overlap, collective tuning, multi-node deployment.

Build production-grade software inside major open-source libraries - vLLM, SGLang, Dynamo, FlashInfer.

Own optimization features end-to-end, from scoping through delivery, collaborating with research, product, and engineering teams worldwide.