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We are looking for an excellent Senior System Validation Engineer!
Our Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables, and software to support networking technologies. Our products optimize data center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of markets including high-performance computing, enterprise, data centers, cloud computing, big data, and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry.

What you'll be doing:

Test Verification and Validation (both HW and SW).

Maintain products quality by improving test stability, coverage, design, and manufacturing process in Mass Production.

Execute tests in different scopes such: as regression, performance degradation, functional, and security; report the progress of testing and provide summary reports of the activity.

Troubleshooting and streamlining/optimizing our testing procedures.

Support Mass production matters.

Debugging production bugs and solving them.

We are seeking a Senior Backend Engineer to join the Sightline detection engineering team. You will design, build, and operate high-scale, low-latency backend services that score and protect web and API traffic against automated abuse, working at the core of our real-time detection platform.
What youll do:
High-Scale Engineering: Design, build, and maintain distributed, high-throughput backend services processing hundreds of thousands of requests per second with strict tens-of-milliseconds latency targets.
End-to-End Ownership: Own services from architecture and implementation to deployment and reliability. This includes full-stack instrumentation (monitoring, alerting, and tracing) to detect and mitigate production issues.
Product Innovation: Implement and evolve real-time detection and decisioning flows within the Sightline Cyberfraud Defense platform, collaborating with security researchers, data science, and product teams.
Cloud-Native Operations: Build and operate services in a Kubernetes environment using a modern GitOps stack (Go, Kafka, Redis, MongoDB, BigQuery, ArgoCD, Pulumi, Crossplane), ensuring robust rollout strategies and safe migrations.
AI-Forward Engineering: Demonstrate a deep passion for the AI-first development frontier and an expert-level ability to leverage assistants and agents to radically accelerate the entire lifecycle - from architectural scaffolding to automated tasks, skills, and complex debugging/testing.
Cross-Functional Collaboration: Partner with adjacent teams to design end-to-end flows that balance security, performance, and customer experience.
Technical Leadership: Contribute to technical design reviews and code reviews, raising the bar for quality and operational excellence across the team.

We are looking for a Backend Software Engineer to join the team and help develop the integration and enforcement layer behind our products. You will work on production software deployed in diverse environments, solve complex web and infrastructure challenges, and own features from design through delivery and operation.
What youll do:
Design, build, and maintain backend and edge components that integrate our detection and enforcement capabilities into customer environments.
Develop reliable, secure, and maintainable services and SDKs, primarily using JavaScript and TypeScript.
Own the full software lifecycle, including technical design, implementation, testing, deployment, monitoring, troubleshooting, and continuous improvement.
Optimize performance and reliability for latency-sensitive components that operate directly in the request path.
Solve portability and integration challenges across different platforms, runtimes, and customer architectures.
Collaborate closely with Product, Security Research, Customer Success Engineering, and other Engineering teams to deliver end-to-end solutions.
Investigate complex production and customer-integration issues and turn what you learn into product and engineering improvements.

Our Networking division is looking for an excellent System Validation Engineer! Our Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables, and software to support networking technologies. Our products optimize data center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of markets including high-performance computing, enterprise, data centers, cloud computing, big data, and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry.

What you'll be doing:
Test Verification and Validation (both HW and SW).
Maintain products quality by improving test stability, coverage, design, and manufacturing process.
Execute tests in different scopes such: regression, performance degradation, functional, and security; report the progress of testing and provide summary reports of the activity.
Troubleshooting and streamlining/optimizing our testing procedures.
Support production matters.

We are looking for best-in-class STA (Static Timing analysis) Physical Design Engineers to join our outstanding Networking DFT team, developing the industry's best high-speed communication devices, delivering the highest throughput and lowest latency! Come and take a part in designing our groundbreaking and innovating chips, enjoy working in a meaningful, growing and highly professional environment where you make a significant impact in a technology-focused company.

What you will be doing:
DFT STA execution, from rtl driven constraints and definitions through DFT constraints quality assurance to STA sign-off.
Be part of a unique team of experts who have deep understanding in all aspects of pre and post silicon.
Be exposed and work on a variety of challenging designs, unique DFT solutions that require deep silicon implementation understanding.
Daily work involves all aspects of static timing analysis - constraints, environment, models generation and timing ECO generation for block level and full chip level.
Taking part in flows development.

Our HW Sustain team in Israel is looking for an board designer to join the sustaining engineering team . The team leads the HW sustaining of networking infrastructure for NVIDIA next-generation data centers focusing on accelerated performance while enabling optimized end to end GPU connectivity.

Our Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables and software to support networking technologies. Our products optimize data center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of markets including high performance computing, enterprise, data centers, cloud computing, big data and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry. Our products are focused on delivering the most optimized power - performance communication solutions for industries like AI, ML, Cloud, Media and Entertainment as well as any other industry that can benefit from our Datastream acceleration.

What you'll be doing:

You will take engineering ownership of networking products once they are released to production

Provide engineering technical leadership for improving product availability, driving cost reduction, and resolving manufacturability issues

Work on debugging and resolving HW related quality issues to improve customers' satisfaction

Required Senior Applied AI Researcher- Sovereign AI Research
About The Position
Nations are waking up to a hard truth: critical intelligence infrastructure built on hyperscaler black boxes isn't a solution it's a dependency. The Sovereign AI Research Group exists to answer that differently.
We're not fine-tuning what already exists. We're rethinking the models architecture from the ground up modular, composable, and built with compute governance as a first-class design constraint, not an afterthought.
We operate under real-world constraints. The interesting problems live at the intersections of disciplines. That's where we operate.
This is a hands-on research role embedded within a team of senior researchers. Day to day includes training models, running benchmarks, synthesize data. The researchers you'll work alongside will challenge you technically and invest in your growth.
Responsibilities:
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

We are looking for an outstanding Manager, Infrastructure Engineering - Networking to lead a high-impact infrastructure engineering team. The team develops and maintains engineering infrastructure solutions that enable R&D teams to provision, validate, test, debug, and recover complex server and networking environments at scale.

In this role, you will lead a team that provides infrastructure platforms and hands-on engineering support for internal customers across firmware, driver, hardware, software, and verification organizations. The position combines deep technical leadership with people management, execution ownership, customer support, and operational excellence in a fast-paced R&D environment. We are looking for a strong technical manager who can grow and mentor engineers, set technical direction, drive recovery of complex systems, optimize customer flows, and deliver reliable infrastructure capabilities in our scale.

What youll be doing:

Lead and grow an infrastructure engineering team responsible for bare-metal provisioning, VM infrastructure, server fleet automation, CI/CD infrastructure, customer-facing debug support, and high-performance networking environments.

Own the teams technical roadmap, priorities, execution plans, and delivery commitments across multiple infrastructure initiatives, while balancing long-term platform improvements with day-to-day customer needs.

Drive ownership of VM box inventory and lifecycle management across many Linux distributions, including image readiness, OS compatibility, package baselines, kernel configurations, provisioning flows, and production availability.

Build infrastructure capabilities that enable engineering and verification teams to run provisioning, testing, validation, and debug workflows efficiently and reliably, without positioning the team as the owner of verification itself.

Lead customer support, debug, and optimization of internal customer flows, including triage, root-cause analysis, bottleneck removal, workflow improvements, and clear communication with engineering stakeholders.

Guide complex system debug and recovery in a firmware R&D environment, including server bring-up issues, driver and firmware interactions, boot failures, networking problems, lab instability, automation failures, and environment recovery.

Provide technical leadership for Linux-based automation platforms, including server lifecycle management, OS installation, kernel configuration, driver setup, inventory management, resource allocation, observability, and production readiness.

Partner closely with firmware, driver, hardware, software, cloud, and verification teams to define requirements, improve reliability, and deliver infrastructure solutions that accelerate engineering productivity.

Were looking for a Software Engineer who is passionate about building high-quality software and solving complex technical challenges. In this role, you'll design and develop production-grade Python services that integrate with third-party devices and platforms, enabling reliable data collection at scale. The systems you build will power our AI platform, providing the critical data foundation behind our products.
Responsibilities
Design and deliver production-grade, high-quality and robust code.
Research a wide range of software and network devices to find the best data collection solutions.
Collaborate with customers to resolve issues and expand Dreams collection portfolio.
Prioritize collection capabilities together with our product team based on customers needs and define milestones.
Work effectively within a team, contributing to a collaborative and innovative development environment.

Required Research Infra Engineer
About The Position
As a Research Infra Engineer, you will build and operate the shared platforms that power our cyber research: data ingestion, connectivity to internal/external systems, scalable analysis environments, and self-serve tools which allow the team moving faster.
Youll partner closely with CyberAI researchers to translate research needs into reliable, secure, cloud-deployed capabilities used across the group. Your goals are to reduces research-toil, improves reproducibility and code quality, and accelerates the path from prototype to shared capability.
Responsibilities
Design, implement, and iterate on internal platforms that support research workflows (e.g., data ingestion, enrichment, indexing, search, labeling, evaluation harnesses, experiment tooling).
Develop durable pipelines and connectors to bring in and normalize research data sources.
Create reusable libraries, templates, CLIs, and services that enable researchers to run analyses and experiments safely and repeatably.
Own deployments, reliability, observability, access control, and cost/performance of the research stack so its usable by all researchers.
Work closely with CyberAI researchers on the development of next-generation artificial cyber researchers and AI-driven analysis capabilities.

Were looking for experienced, hands-on researchers who have repeatedly taken complex AI capabilities from initial problem definition to real-world use. Expect scarce data, noisy labels, and problems without an established playbook. Youll have the autonomy to shape the approach-and the responsibility to make it work.
Responsibilities
Our Research Tracks:
Were hiring across four tracks. We expect deep expertise in at least one, not mastery of all four.
Agents: Self-improving agents, learning from execution traces, and user feedback. Genetic and evolutionary optimization of workflows, tools, and code
NLP: Reinforcement learning for language models, distillation, retrieval and embeddings, named-entity and relation extraction, and multilingual learning.
Vision & Audio: Visual and speech understanding, detection and segmentation, multimodal representation learning, grounding, and cross-modal retrieval.
Machine Learning: Representation and graph learning, probabilistic and causal modeling, optimization, and learning with limited or noisy data.
What Youll Own:
Take research from an open-ended problem to a working capability: define success, develop the data and methods, run rigorous experiments to make it work. Work closely with engineering through deployment, measuring quality, efficiency, not just benchmark scores. Drive progress through technical blockers, adapt when an approach fails, and strengthen the team through collaboration, technical review, and mentoring.

The PerfTech team is looking for a talented C++ Software Engineer to help build the next generation of AI-powered developer tools. You will apply strong C++ and software-engineering fundamentals while gaining hands-on experience with agentic workflows, retrieval systems, and AI services.

In this role, you will contribute to Genie, our company-wide AI knowledge and developer-productivity service. You will work across C++ tools and AI services to help engineers find information, understand complex systems, and work more effectively.

What Youll Be Doing:
Develop production-quality C++ components, APIs, and integrations for our AI-powered developer-tools ecosystem.
Build capabilities connecting native C++ tools with Genies retrieval and agentic features.
Contribute to agentic workflows, retrieval systems, ingestion pipelines, MCP tools, APIs, and enterprise integrations.
Build benchmarks and improve retrieval quality, reliability, performance, and resource usage.
Own features from investigation and design through implementation, testing, and delivery.
Collaborate with graphics, software, and hardware teams developing performance-analysis and developer tools.

Required Security Researcher
About The Position
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world security research. You'll help us harness the power of our trillions of security signals to rapidly diagnose and alert the latest attacker behaviors, drive critical context-rich signals, construct new tools and automations to support customers, identify threats, and detect advanced attacker techniques.
Responsibilities
Analyze various network devices, configurations and security products
Implement methods and algorithms to discover network topology, relationships between devices and potential lateral movement paths
Conduct network security assessments to identify weaknesses in customers network infrastructure, and recommend mitigations to monitor and limit unauthorized access
Develop research tools and frameworks to perform automatic analysis of network devices and security products
Research and analyze network-related cybersecurity threats and trends
Work closely with other internal engineering and AI teams to integrate new capabilities into our platform and guide cross-product architectural decisions
Act as a security subject matter expert for multidisciplinary teams.

We are now looking for a Senior Chip Design Verification Engineer for the Switch Silicon group.

As a Chip Design Engineer at NVIDIA's Networking business unit, you'll join a group of passionate engineers to design and implement the next generation state of the art Switch Silicon chips. In this position, you'll make a real impact in a dynamic, technology-focused company while developing the industry's best high-speed communication devices, delivering the highest throughput and lowest latency!

What you'll be doing:
Work in a combined design and verification team which develops some of the switch silicon core units.
Build reference models, verify and simulate chip blocks/entities according to specifications.
Work closely with multiple teams within organizations such as Architecture, Micro- Architecture, and FW.

We are looking for a talented AI Solutions Engineer to join our innovative AI team. In this role, you will act as a bridge between our AI capabilities and internal customers, helping teams effectively adopt and integrate cutting-edge AI based solutions. Our team develops advanced AI applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will play a key role in ensuring these technologies deliver real value by working closely with users and contributing hands-on development. We are looking for a motivated teammate who enjoys working with technology, people and developing new capabilities.


What you'll be doing:

Lead technical engagements to showcase AI capabilities and demonstrate best practices.

Support integration of AI solutions into existing systems and workflows.

Guide users on how to effectively use AI tools and platforms to maximize impact.

Develop and customize AI solutions (e.g., RAG pipelines, LLM-based applications, evaluation, agents, etc.) based on customer use cases while ensuing high reliability.

Troubleshoot technical issues and provide hands-on support during onboarding and adoption.