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לפני 19 שעות
Location: Yokne`am and Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
What we need to see:

B.Sc. or M.Sc. in Computer Science, Computer Engineering, Software Engineering, or equivalent technical experience.

8+ overall years of experience and deep expertise in High Performance Networking, RDMA, and Systems level performance.

3+ years of experience as an engineering team manager leading technical performance or R&D teams.

Hands-on experience analyzing and optimizing collective communication (e.g., NCCL, MPI) and network traffic patterns for large-scale distributed AI workloads (LLM training and inference).

Hands-on experience designing, deploying, and customizing Grafana dashboards for cluster monitoring, alerting, and data visualization.

Exceptional cross-team leadership, analytical thinking, and communication skills to drive alignment across hardware, software, and architecture groups.


Ways to stand out from the crowd:

Proven track record of optimizing NCCL, RDMA/RoCEv2, and custom collective algorithms specifically tailored for multi-thousand GPU deployments running LLMs or Mixture-of-Experts (MoE) architectures.

Deep experience tuning advanced network traffic mechanisms such as adaptive routing, PFC/ECN congestion control, and packet-spraying technologies.

Experience building autonomous performance-driven tools, AI-assisted root cause analysis agents, or automated regression frameworks for continuous cluster-level performance evaluation.

Hands-on experience developing custom Grafana plugins, complex dashboard panels, or integrated alert management workflows using PromQL/LogQL for hyperscale or HPC environments.
This position is open to all candidates.
 
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4 ימים
חברה חסויה
Location: Yokne`am
Job Type: Full Time
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.
Requirements:
What we need to see:

B.Sc. or M.Sc. in Computer Science, Computer Engineering, Software Engineering, or equivalent experience.

5+ years of experience in performance analysis, systems engineering, or HPC/AI infrastructure.

Demonstrated expertise in performance analysis skills and methodologies.

Hands-on experience with high-performance networking (RDMA, MPI, NCCL, congestion control).

Strong understanding of system performance metrics (latency, throughput, resource utilization).

Exposure to hardware, firmware, or embedded telemetry environments.

Strong analytical, problem-solving, and communication skills.

Ability to work effectively in cross-functional, fast-paced R&D teams.


Ways to stand out from the crowd:

Knowledge of CUDA, NCCL internals, and congestion control algorithms.

Deep system-level understanding of CPU architectures, GPUs, HCAs, memory, and PCIe.

Experience with NVIDIA GPUs, CUDA, and deep learning frameworks such as PyTorch or TensorFlow.

Experience with cloud platforms.

Proficiency in Python; experience with Bash and C/C++ is a plus as well as a strong experience working in Linux environments.
This position is open to all candidates.
 
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5 ימים
Location: Tel Aviv-Yafo and Yokne`am
Job Type: Full Time
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.
Requirements:
What we need to see:

B.Sc. Or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.

3+ years of relevant industry or research experience.

Strong machine learning or data science background, with hands-on experience in LLMs, generative AI, or deep learning systems.

Strong systems-level thinking, capable of estimating end-to-end requirements across the AI stack.

Shown ability to translate research findings and product requirements into clear software and hardware specifications.

Excellent research skills, including the ability to digest academic papers, self-learn new domains, and independently test hypotheses.

Advanced programming skills for performance modeling, data analysis, and prototyping.

Excellent communication skills, demonstrating proficiency in presenting complex technical findings clearly and confidently.


Ways to Stand Out from the crowd:

Experience with distributed training, distributed inference, or large-scale AI serving systems.

Experience in Agentic programming, and AI tools

Familiarity with GPU clusters, collective communication, storage systems, or AI networking bottlenecks.
This position is open to all candidates.
 
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3 ימים
Location: Yokne`am
Job Type: Full Time
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.
Requirements:
What we need to see:
B.Sc. in Computer Science, Electrical Engineering, or related field (or equivalent experience).
8+ years of experience in networking, system validation, or related engineering roles.
Strong hands-on experience with Linux-based systems.
Deep understanding of networking protocols (TCP/IP, UDP, Ethernet, VLANs, L2/L3).
Experience with routing, switching, and modern data center network architectures.
Strong troubleshooting, debugging, and analytical skills in distributed environments.
Experience with test methodologies (functional, regression, performance, scale).
Scripting or programming experience (Python, Bash, etc.).
Independent, fast learner with strong ownership and communication skills.

Ways to stand out from the crowd:
Experience with RDMA technologies (RoCE / InfiniBand).
Knowledge of congestion control algorithms and performance tuning.
Familiarity with AI workloads and their networking requirements.
Experience with HPC environments and benchmarking tools.
Background with virtualization or container technologies (Kubernetes, KVM, etc.).
This position is open to all candidates.
 
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5 ימים
Location: Yokne`am
Job Type: Full Time
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.
Requirements:
What We Need To See:
B.Sc. or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
Experience in performance analysis, systems engineering, networking, or HPC/AI infrastructure.
10+ years of software engineering experience, including 4+ years in a leadership or management role.
Experience with high-performance networking technologies such as RDMA, RoCE, InfiniBand, Ethernet, MPI or NCCL.
Hands-on experience with system performance analysis, benchmarking, profiling, and root-cause analysis.
Understanding of host architecture, including CPUs, memory hierarchy, NUMA, PCIe, Linux OS, drivers, firmware, and DPU/NIC interactions.
Experience creating performance test plans for pre-silicon or post-silicon phases.
Programming or scripting experience with Python and Bash; C/C++ experience is helpful.
Ability to communicate technical findings clearly and work across engineering teams.

Ways To Stand Out from the Crowd
Experience with NICs or DPU architecture, networking offloads, host datapath behavior, networking services, or DPU offloads.
Experience with AI/HPC cluster performance, distributed training, inference workloads, collective communication libraries, telemetry pipelines, benchmark automation, CUDA, NCCL internals.
Linux kernel networking, DPDK, OVS, storage acceleration, or security offloads can also help you succeed in this role.
This position is open to all candidates.
 
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לפני 19 שעות
Job Type: Full Time
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.
Requirements:
What We Need To See:

B.Sc. or M.Sc. in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience.

9+ years of experience in networking, system software, embedded software, firmware, or datacenter infrastructure.

Proven experience in software architecture, or technical leadership roles.

Deep understanding of networking concepts and protocols such as Ethernet, TCP/IP, RDMA/RoCE, congestion control, QoS, virtualization overlays, and traffic management.

Strong background with DPUs, SmartNICs, or other high-performance networking devices.

Experience with system management, provisioning, monitoring, telemetry, diagnostics, or lifecycle-management flows.

Familiarity with management protocols and frameworks such as Redfish, PLDM, MCTP, IPMI, gNMI, SNMP, Netconf, REST, or gRPC-based APIs.

Ability to lead cross-functional architecture discussions across software, firmware, hardware, validation, product, and customer-facing teams.

Excellent written and verbal communication skills, including the ability to create clear architecture documents and present trade-offs.


Ways To Stand Out From The Crowd:

Experience defining software architecture for DPU products, including management, telemetry, QoS, performance, security, virtualization, or offload features.

Hands-on background with Linux networking, device drivers, firmware, embedded Linux, BMC software, DOCA, DPDK, OVS or Kubernetes networking.

Experience with performance counters, profiling tools, eBPF, Prometheus, Grafana, dashboards, heat maps, or large-scale telemetry systems.

Experience in defining and developing GAI-based analysis tools to extract insights from telemetry data and streams.

Background in RAS, diagnosability, serviceability, field failure analysis, production debug, or customer escalation handling.
This position is open to all candidates.
 
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3 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
What we need to see:

BSc or above in Computer Science, Electrical Engineering, or a related field

5+ years of recent hands-on coding experience with strong proficiency in C++ and Python. You must be comfortable navigating, optimizing, and contributing to a complex, large-scale codebase.

End to end system perspective - capable of bridging the gap between hardware behavior, micro-architecture, and software performance (latency/throughput).

Project ownership capability with proven ability to lead technical initiatives, prioritize features, and manage project lifecycles autonomously with minimal supervision.


Ways to stand out from the crowd:

Strong background in communication networks technology. Deep understanding of Ethernet, NVLink, and/or Infiniband technologies, data center infrastructure, and network protocols.

Familiarity with discrete event simulators (e.g., OMNeT++, SystemC, or proprietary architectural simulators).

 Advanced degree or experience focusing on computer architecture, algorithms, networking, or distributed systems.
This position is open to all candidates.
 
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4 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
What we need to see:

B.Sc., M.Sc., or equivalent experience in Computer Science or Computer Engineering.

5+ years of hands-on software engineering experience in performance-critical systems.

Solid understanding of deep learning architectures (Transformers, SSMs, MoE, ).

Experience with systems where hardware constraints matter: GPU programming, memory hierarchy, networking, or distributed computing.

Strong software engineering fundamentals: clean design, extensibility, testability. Good judgment about when complexity is warranted.

Effective communicator who works well across teams and time zones.

Experience optimizing deep learning workloads on our GPUs using roofline models, Nsight/PyTorch profilers and end-to-end traces.


Ways to stand out from the crowd:

Contributions to open-source inference runtimes and libraries - vLLM, SGLang, FlashInfer, Dynamo or similar.

Hands-on work with LLM quantization (FP8, NVFP4, MXFP8, mixed-precision) and practical understanding of numerical precision tradeoffs.

Track record with distributed inference at scale: tensor parallelism, pipeline parallelism, expert parallelism, disaggregation, multi-node orchestration.

Deep knowledge of the latest LLM architectural trends: multi-token predictors, sparse hybrid models, attention and state-space mechanisms.

Experience with performance modeling and simulation-to-silicon correlation.
This position is open to all candidates.
 
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5 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Network Solution Verification Manager to join our R&D organization, leading the validation of our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will build and lead a team of validation engineers, owning the strategy, methodology, and execution of simulation-based validation frameworks that ensure our networking solutions meet the highest standards of quality, scale, and real-world applicability before reaching customers.


What you'll be doing:
Leading and managing a team of network validation engineers responsible for end-to-end validation of our customer-facing networking solutions at scale, using a dedicated E2E simulation cluster environment.
Defining the overall validation strategy and roadmap - establishing simulation methodologies, test coverage frameworks, and quality gates that align with product milestones and customer use cases.
Pioneering the use of agentic AI flows within the validation organization - leading the team to design, build, and operate AI-driven agents capable of autonomously performing regression analysis, identifying coverage gaps, generating new test cases, and implementing validation code. These agentic workflows will continuously learn from simulation results and product changes, dramatically accelerating the team's ability to scale test coverage and respond to emerging quality signals without manual intervention.
Overseeing the design and continuous improvement of automated regression suites for networking protocols and large-scale simulation runs, ensuring scalable, repeatable, and high-confidence validation outcomes.
Establishing a rigorous regression analysis culture - guiding the team in identifying trends, root causes, and systemic coverage gaps, and ensuring timely resolution in collaboration with engineering stakeholders.
Serving as the primary validation partner to Design, Architecture, and NCS teams - translating solution requirements into simulation scenarios, providing early-cycle quality feedback, and influencing product direction.
Analyzing customer-reported networking solution issues, driving test gap analysis, and ensuring robust regression coverage that prevents recurrence.
Staying current with emerging networking standards, simulation technologies, and industry best practices to continuously evolve the team's validation capabilities.
דרישות:
What we need to see:
B.Sc. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
3+ years of experience in a leadership or management role, leading software or hardware validation/test engineering teams.
7+ years of overall experience in network validation, network testing, or systems verification.
Proven track record of building and executing test automation strategies for network or distributed systems at scale, with hands-on background in Python-based automation.
Strong understanding of regression analysis methodologies - ability to drive actionable conclusions from large-scale test result datasets and translate them into engineering improvements.
Demonstrated ability to collaborate cross-functionally with architecture, design, and product teams in a fast-paced, multi-timezone environment.
Strong verbal and written communication skills, with experience presenting validation strategies and quality metrics to senior leadership.


Ways to stand out from the crowd:
Deep understanding of networking protocols and architectures (e.g., BGP, EVPN, VXLAN, RDMA/RoCE, Ethernet, IP routing, L2/L3 switching).
Experience with network simulation or emulation environments (e.g., Containerlab, GNS3, SONiC testbeds, or equivalent platforms) and the ability to guide teams in leveraging them effectively.
Experience managing validation of data center networking solutions or hyperscale network environments (spine-leaf, fat-tree, or Clos top#EN המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
5 ימים
חברה חסויה
Job Type: Full Time
We are seeking a Director of Software Architecture to lead and accelerate the evolution of next-generation AI data center and networking technologies. This role is designed for a hands-on, execution-driven leader who pushes boundaries, translates vision into reality, and delivers high-impact solutions at scale. You will operate at the intersection of innovation, architecture, and delivery-shaping the future of AI networking and infrastructure.

What you will be doing:
Drive identification, evaluation, and rapid adoption of emerging technologies, ensuring strong alignment with strategic roadmap and measurable business outcomes.
Lead the design and delivery of advanced networking applications, leveraging data plane programming and modern networking protocols to solve complex, large-scale challenges.
Architect solutions across AI data center environments, integrating GPU-based systems, hardware acceleration, and high-performance networking.
Act as a thought leader and industry influencer-engaging directly with customers, publishing technical content, and representing us at key conferences and forums.
Define and execute a bold architectural vision for our networking in close collaboration with cross-functional software and hardware leaders.
Requirements:
What we need to see:
M.Sc. or PhD. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
12+ years of deep experience in software architecture, systems design, and applied research.
8+ years of proven leadership, building and driving high-performing engineering teams in fast-paced environments.
Strong expertise in AI inference technologies, frameworks, and large-scale distributed systems.
Hands-on experience with networking protocols (e.g., TCP/IP, RDMA, RoCE, InfiniBand) and data center networking architectures.
Deep familiarity with AI DC architectures, hardware acceleration technologies, and SDKs (e.g., DOCA, CUDA or similar).
Experience with AI data center design, including compute, networking, and AI storage systems.
Exceptional communication and influence skills, with a demonstrated ability to align stakeholders and drive decisions across complex organizations.

Ways to stand out from the crowd:
A track record of aggressively prototyping, validating, and scaling new ideas into production.
Strong foundations in system software, including operating systems and low-level architecture.
Experience with hyperscale cloud and AI data center environments.
Expertise in AI storage systems, high-performance computing (HPC), and end-to-end accelerated infrastructure.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8767985
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
5 ימים
Location: Tel Aviv-Yafo and Yokne`am
Job Type: Full Time
We are seeking a Network Solution Verification Engineer to join our R&D organization, focused on validating our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will be a hands-on technical contributor at the intersection of networking, automation, and AI-driven validation - designing and implementing the simulation frameworks, agentic workflows, and regression pipelines that ensure our networking solutions meet the highest standards of quality and real-world applicability before reaching customers.


What you'll be doing:
Designing and implementing end-to-end validation frameworks for our customer-facing networking solutions at scale, leveraging a dedicated E2E simulation cluster environment.
Writing, maintaining, and extending automated test suites and regression pipelines for networking protocols and large-scale simulation runs, ensuring repeatable, high-confidence validation outcomes.
Performing deep regression analysis on simulation results - identifying failure trends, isolating root causes, and delivering clear, actionable findings to architecture and design teams.
Developing agentic AI flows that autonomously perform regression analysis, detect coverage gaps, generate new test cases, and implement validation code - continuously learning from simulation results and product changes to accelerate coverage without manual intervention.
Integrating validation pipelines into CI/CD workflows to enable continuous, automated regression at scale, working closely with DevOps and platform teams.
Collaborating closely with Design, Architecture, and NCS teams to understand solution requirements, translate them into simulation scenarios, and provide early-cycle quality feedback that influences product direction.
Analyzing customer-reported networking issues, mapping them to simulation coverage gaps, and building targeted test cases that prevent regression.
Continuously exploring new simulation technologies, agentic frameworks, and networking standards to evolve and improve the team's validation methodology.
Requirements:
What we need to see:
B.Sc. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
3+ years of hands-on experience as a software developer.
Strong proficiency in Python for test automation, tooling development, and pipeline implementation.
Hands-on experience with network simulation or emulation tools (e.g., Containerlab, GNS3, SONiC testbeds, or equivalent platforms).
Proven experience designing and building simulation agents or traffic generators that mimic real-world networking behavior at scale.
Solid experience with agentic AI frameworks and LLM-based automation (e.g., LangChain, LangGraph, AutoGen, or similar) and practical ability to apply them to validation and test generation workflows.
Strong command of regression analysis methodologies - able to triage, classify, and extract actionable conclusions from large-scale test result datasets.
Comfortable operating in a fast-paced, cross-functional, multi-timezone engineering environment with strong verbal and written communication skills.

Ways to stand out from the crowd:
Hands-on experience validating data center networking solutions or hyperscale network environments (spine-leaf, fat-tree, or Clos topologies).
Familiarity with our networking products - BlueField DPUs, ConnectX NICs, Spectrum switches, or the DOCA software stack.
Deep understanding of networking protocols and architectures (e.g., BGP, EVPN, VXLAN, RDMA/RoCE, Ethernet, IP routing, L2/L3 switching).
Hands-on experience building agentic pipelines for automated test generation, result triage, or validation code synthesis - including prompt engineering and tool-use patterns for LLM agents.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8768268
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