דרושים » הנדסה » Software Engineer - AI Datacenter Networking

we are looking for a Software Team Lead.
Job Summary
Develop and optimize high-performance software for AI datacenter networking, implementing NOS enhancements, smart NIC integration, and specialized routing features for AI workloads.
Key Responsibilities:
Implement network operating system features for AI-optimized switching scenarios
Integrate smart NIC solutions for end-to-end AI-optimized networking
Create monitoring and telemetry collection mechanisms for datapath analysis
Implement load balancing algorithms optimized for AI workload patterns
Debug and optimize datapath performance bottlenecks
Collaborate with QA teams on feature testing and validation

We are looking for an outstanding Senior Networking Software Architect to join the NIC/DPU Software and Firmware Architecture group. In this role, you will help define the next generation of our datacenter and AI networking platforms, with focus on DPU management, QoS, performance, telemetry, and software architecture across stacks. You will work closely with hardware designers, firmware/kernel driver teams, system engineers, validation, product management and customers. The role spans early architecture definition, pre-silicon design, bring-up, and production readiness for large-scale AI and cloud datacenter deployments.

What Youll Be Doing:

Own software and system architecture for next-generation DPU management, QoS, performance, telemetry, and observability features.

Define end-to-end control and management flows across DOCA, host drivers, embedded firmware, BMC, management controllers and external management systems.

Specify telemetry and observability requirements, including counters, logs, traces, events, health monitoring, debug data, and streaming telemetry.

Define management interfaces and APIs for configuration, provisioning, lifecycle operations, diagnostics, and field serviceability.

Write clear architecture specifications, interface definitions, flow diagrams, and design documents for software, firmware, and system teams.

Partner with R&D teams to translate high-level architecture into implementable designs and guide features through development, validation, silicon bring-up, and production.

Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture.

Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs.

We are seeking a highly skilled and modern software engineer to develop and prototype brand new advancements in distributed training and inference using our Spectrum-X AI fabric. This role offers a rare chance to pioneer AI and networking technology, contributing to ground-breaking projects that will define the landscape of large-scale AI systems. Improve AI app-networking connection by refining communication, crafting congestion control, coding NIC firmware, and expanding switch SDK features for enhanced AI factory efficiency. Your work impacts large AI system development, scaling, and speed.

What youll be doing:

Prototype end-to-end solutions to improve distributed training and disaggregated inference performance.

Analyze and optimize communication flows across application, transport, and network layers.

Develop system software spanning communication libraries, drivers, and firmware integrations.

Collaborate with hardware, firmware, and SDK teams to co-design network features.

Validate and integrate prototypes into our AI infrastructure and products.

We are seeking a highly skilled and versatile Performance Research and Analysis Manager to join our Performance Group. This role will drive end-to-end performance strategy and execution for next-generation our data centers and solutions based on GPU systems, NIC, Switch, DPU and Networking technologies. The ideal candidate will oversee, evaluating, and optimizing end-to-end AI GPU cluster-level performance for scaling out large scale distributed training and inference jobs communication. The role will focus heavily on RDMA, Networking Protocols, Collective Communication, Congestion Control, and Load Balancing algorithms. Secondarily, you will lead our DPUs and Storage technologies for N-S use cases to support AI Inference jobs. Third, you will drive our Performance Dashboards and Observability for cluster-level performance analysis from a stream line telemetry across NICs, Switches, GPUs, and NVlink.

What you'll be doing:

Drive end-to-end performance strategy, characterization, test plans, and optimization for next-generation our AI GPU clusters, focusing on large-scale distributed training and inference workloads.

Deeply evaluate and optimize our Networking core technologies performance, including RDMA/PRDMA, networking protocols, collective communication (NCCL), congestion control, and load-balancing algorithms.

Work on performance research and analysis of NVIDIA DPUs and storage technologies in North-South (N-S) use cases and deployment scenarios to maximize performance and efficiency for AI inference jobs.

Drive the strategy for performance observability and dashboards across next-generation NVIDIA data center solutions and supercomputers by leveraging scalable, streamlined telemetry pipelines to build performance dashboards and automated analytics based on real-time performance metrics across NICs, Switches, GPUs, and NVLink boundaries.

Perform deep root-cause analysis (RCA) on complex multi-node performance bottlenecks, driving actionable mitigation plans across hardware, firmware, and software teams.

Required Software Engineer III, Cloud Networking
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
This Team owns the core data plane infrastructure for all NAT-based products within the Andromeda network stack (e.g., private service connect (PSC) and Cloud network address translation (NAT). These products serve as critical entry and exit gateways that securely connect Cloud customers to their services and networks.
Responsibilities
Design, develop, test, and maintain high-performance software for our Cloud's core networking and secure connectivity platforms.
Manage complex scalability, resource efficiency, and performance optimization challenges to evolve our cloud networking datapath.
Collaborate with cross-functional engineering partners to define and build new network architectures and routing methods.
Manage individual project priorities, deadlines, and deliverables, ensuring high engineering velocity and robust code quality.
Participate in operational rotations, monitor production health, and troubleshoot packet latency or connectivity issues to keep our global systems healthy.

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 an outstanding engineer to join our software architecture group and help shape the next generation of our networking products, SmartNICs, and DPUs. In this role, you will work closely with system architects, software/firmware engineers, hardware designers and product stakeholders to define component-level and system-level solutions for advanced datacenter platforms.

You will join a team working at the intersection of AI networking, virtualization, operating systems, security, management, and programmable acceleration. Our mission is to push the boundaries of modern datacenter infrastructure and help define the platforms of tomorrow.

What Youll Be Doing:

Work with architects and engineers to define software architecture for our networking devices, SmartNICs, and DPUs.

Analyze system requirements across networking protocols, virtualization, operating systems, security, management, and services.

Research new ideas, evaluate design alternatives, and build proof-of-concept models, simulations, and prototypes.

Collaborate with software, firmware, and hardware teams on HW/SW co-design, performance, scale, and resource-utilization challenges.

Learn complex datacenter technologies and turn them into clear architecture proposals, design documents, and technical presentations.

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 are looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need an individual contributor who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference.
- Implement and validate LLM architectures end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation, testing, and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.

we are looking for a Software Engineer Infra.
Responsibilities:
- Design and develop the core infrastructure components that power our products across a large-scale distributed system.
- Own and evolve key infrastructure domains such as high-availability, data-management, security, and telemetry.
- Produce excellent software design, write clean and efficient code, and debug complex issues across the stack.
- Mentor and guide junior engineers, sharing knowledge and raising the technical bar of the team.
- Turn ambitious, out-of-the-box ideas into real, production-grade value for our customers.