לוח משרות דרושים מהנדס תוכנה ברעננה

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.

As a Graph Compiler Software Manager, you will lead the development of next-generation graph compiler technology. This compiler is a cornerstone of AI software offering, empowering customers to optimize, map, and execute complex neural networks across architectures with extraordinary efficiency. You will lead a group of talented engineers and team leaders working across domains such as compiler optimizations, graph-level transformations, operator mapping, scheduling, and code generation. We are seeking a visionary and technically strong leader with passion for excellence and impact in one of the most fascinating areas of AI and deep learning.

Key Responsibilities:

Lead the design and implementation of innovative graph compilation flows for AI workloads, from high-level optimizations to hardware-specific backends. Build and guide a strong, innovative, and results-driven compiler team that thrives on solving complex technical challenges. Collaborate with hardware architecture, VLSI, and software framework teams worldwide to ensure seamless integration and maximum performance. Lead the end-to-end delivery of graph compiler components while meeting aggressive KPIs. Establish and execute group planning processes to ensure timely and high-quality delivery. Provide technical and managerial guidance to team leaders and engineers. Define and drive compiler optimization strategies for AI and deep learning workloads.

Own and design key components of the Edge AI software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

We are looking for talented, highly motivated Senior Java Software Engineers to join our Cloud Analytics group. If youre passionate about building modern cloud architectures and enjoy solving complex engineering challenges, this role is for you.
You will help design and develop large‑scale, AWS‑based systems that power the global CXone cloud platform. The applications you build are deployed across multiple regions and support hundreds of enterprise customers worldwide.
How will you make an impact?
Design and implement scalable microservices using AWS technologies.
Develop high‑quality services in a Java Spring Boot environment.
Participate in the full feature lifecycle-from design to implementation.
Analyze requirements and create clear, comprehensive design documentation.
Review and refine designs with peers and stakeholders.
Collaborate closely with the team to iterate on architecture and features.
Apply agile methodologies with AI tools to deliver reliable, high-impact capabilities efficiently.

We are looking for an experienced Software Engineer to join our team with a focus on services and infrastructure development, while being comfortable contributing across the full software stack when required.

This role is well suited to an engineer who enjoys designing and building scalable backend services, integrating them with infrastructure platforms, and contributing to end-to-end solutions that support sophisticated engineering workflows. While some components may include frontend elements, the primary emphasis is on service architecture, APIs, data handling, and system reliability.

In this role, you will collaborate closely with engineers and partners across the organization to design, deliver, and evolve maintainable solutions that underpin GPU software engineering infrastructure. You will also contribute to technical direction, mentor others, and help shape the long-term evolution of our platforms.

Responsibilities:
Design, develop, and maintain scalable backend services using Python, Go or similar languages, with the ability to contribute to full-stack solutions where appropriate.
Take ownership of services across their lifecycle, from design and implementation through deployment and production support.
Design and evolve APIs and service interfaces that support tooling, automation, and infrastructure workflows.
Contribute to end-to-end feature development, spanning backend services, APIs, and selective frontend components where they support infrastructure use cases.
Collaborate closely with teams across tooling, automation, and infrastructure to ensure seamless service integration.
Improve system reliability, performance, and scalability through thoughtful design and continuous optimization.
Contribute to infrastructure modernization initiatives, including cloud-based and containerized deployments.
Follow and promote standard methodologies for code quality, testing, documentation, and design reviews.

seeking a hands-on Embedded Software Technical Lead to play a key role in the design and development of firmware for our next-generation rider products. This role is focused on deep technical ownership, system -level thinking, and high-quality implementation, and is ideal for an experienced Embedded engineer with a strong algorithmic background and solid architectural understanding-who can also mentor and lead a small team of 2-3 Embedded engineers while remaining highly hands-on in day-to-day development. What Youll Do
* Take hands-on responsibility for the design and implementation of Embedded software architecture for new wireless communication devices (ARM Cortex-M, RTOS, ultra-low-power systems).
* Design, implement, and optimize complex Embedded algorithms, including Real-Time control flows, communication logic, and audio/ DSP -related pipelines.
* Write, review, and maintain high-quality, production-grade C / C ++ code.
* Contribute to system -level architectural decisions and ensure scalable, robust firmware design.
* Define and promote coding standards, design patterns, and best practices across the firmware domain.
* Act as a technical focal point for debugging, root-cause analysis, and performance optimization of complex issues.
* Lead a small team of 2-3 programmers/engineers: provide technical direction, help with task breakdown and prioritization, and ensure high-quality delivery.
* Mentor engineers through design reviews, technical discussions, pairing, and hands-on collaboration-raising the teams engineering bar.
* Work closely with Hardware, QA, Mobile App, Cloud, and Product teams to deliver integrated, end-to-end solutions.
* Participate in technical roadmap discussions and evaluation of tools, technologies, and wireless stacks.

We are looking for an AI & Automation Engineer to design, build, and enable enterprise AI infrastructure and automation solutions.
This role focuses on AI architecture, workflow automation across IT and business applications, and monitoring, governance, and cost management of AI tools and agents.
You will work at the intersection of AI platforms, IT operations, and business automation, enabling scalable, secure, and cost-effective AI adoption across the organization.
Responsibilities:
Select and integrate AI tools, frameworks, and platforms aligned with enterprise IT standards.
Ensure scalability, security, reliability, and compliance of AI infrastructure.
Enable AI solutions from concept to production, including:
AI-powered IT tools
AI agents and copilots
AI services integrated into business applications
Collaborate with IT, DevOps, Security, and Business teams to deploy AI solutions smoothly.
Build reusable AI enablement patterns, templates, and best practices.
Automation of Workflows
Design and implement automation of IT and business workflows using AI and orchestration tools.
Integrate AI agents into:
IT operations (ITSM, monitoring, incident response)
Business applications and internal systems
Improve efficiency, reliability, and user experience through intelligent automation.
AI Monitoring, Usage & Financial Governance
Define and implement monitoring for AI systems, including:
Usage tracking
Performance and reliability
Model and agent behavior
Track and analyze financial usage and cost of AI tools, APIs, and platforms.
Establish governance frameworks for responsible and controlled AI usage.

Execute comprehensive testing of AI datacenter networking solutions, focusing on SONiC-based systems, smart NIC integration, and high-performance networking for AI workloads.
Key Responsibilities:
Design large scale testing topologies with GPU/Traffic Generators and execute test cases for SONiC/our company network operating system functionality.
Validate smart NIC performance and integration with SONiC datapath
Perform functional, performance, and stress testing of AI networking scenarios
Develop automated test scripts for regression testing and continuous validation
Execute interoperability testing between different hardware vendors and software versions
Validate RDMA, high-speed Ethernet performance for AI workloads
Test failover scenarios and network resilience under various failure conditions
Document test results, file detailed bug reports, and track issue resolution
Collaborate with development teams to reproduce and isolate defects
Participate in customer proof-of-concept testing and field issue reproduction.

We are seeking an Embedded Software Technical Lead who combines strong hands-on development expertise with the ability to guide a team technically. This role involves leading the design and development of new features, ensuring code quality, supporting customers when needed, and fostering collaboration and continuous improvement across the organization.
Responsibilities
Engage in hands-on software development, debugging, and troubleshooting on embedded targets, working closely with the team.
Lead technical efforts for new features, ensuring reliability, scalability, and high performance.
Improve software quality by conducting code reviews, mentoring team members, and promoting best practices.
Provide customer support when necessary, addressing technical issues efficiently.
Encourage a culture of open communication and feedback within the team and across teams.

We are looking for a highly professional Technical Marketing Engineer (TME), to dive into our technology, master our lab and produce high-quality technical marketing content for our AI-infrastructure marketing campaigns. This position plays a crucial role in translating our engineering know-how into marketing content. It requires a blend of deep networking technical expertise, hands-on capabilities, strong communication skills, and a passion for translating complex technical information into compelling marketing messages that resonate with target audiences.
Responsibilities 
Collaborate with our research lab, engineering and delivery services to map technology, architecture, and deployment know-how.
Create high-quality content (reference designs, deployment and configuration guides, whitepapers, case studies, blog posts, demos etc.)
Support sales and channels in customers and partners' meetings.
Travel to support tradeshows, and customers and partners' events.

We are looking for a Senior HPC and AI Cluster Administrator to join the Networking clusters solutions HPC/AI Infrastructure team. We are building supercomputers and AI clusters based on groundbreaking technologies. We are looking for a system administrator to be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing

You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. Does this sound like you? If so, we would love to hear from you!

What you will be doing:

Deploy, manage and maintain large scale HPC/AI clusters.

Managing Linux job/workload schedules and orchestration tools.

Support and maintain continuous integration and delivery pipelines.

Troubleshooting and fixing, bottom up from bare metal, operating system, software stack and application level.

Supporting Research & Development activities and engaging in POCs/POVs for future improvements.

We are seeking an experienced IT/Lab Manager to lead the planning, deployment, and operations of our physical lab environment and IT systems. This role will focus on building and maintaining scalable, reliable, and secure environments to support engineering teams involved in research, quality assurance, validation, and related activities. It will also support internal collaborators. You will have an outstanding opportunity to drive innovation in a multidimensional, technology-focused company that is crafting the future of data-center and lab technologies. If you bring perfection and creative thinking while solving issues as they arise, and enjoy working with distributed teams - your place is with us!

What Youll Be Doing:
Own day-to-day operations, planning, and roadmap for the engineering lab and IT infrastructure (servers, storage, networking, and related services).
Lead and mentor an IT/Lab team, driving guidelines, standards, and a culture of ownership, partnership, and continuous improvement.
Collaborate closely with R&D, QE, Verification, and other engineering teams to design, provision, and maintain environments that meet their performance, reliability, and security needs.
Lead all aspects of running data center and lab operations, including rack layout, cabling, power and cooling, hardware lifecycle, and resource availability.
Lead procurement and vendor management for hardware, software, and services, including evaluation, negotiation, and ongoing relationship management.
Implement and maintain automation for system provisioning, configuration, and operations using tools such as shell/Perl/Ansible.
Design and maintain monitoring, logging, and alerting for servers, network, and storage systems to ensure high availability and rapid incident response.
Investigate and resolve sophisticated infrastructure issues across OS, networking, storage, virtualization, and application layers.

We are looking for an excellent Software Director for the Switch management SW Group. You will join the NVIDIA switch Management team and take our product to next level, working closely with various SW teams and verification teams and gain deep understanding of NVIDIAs products and technologies. NVIDIA is 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

What you'll be doing:

Be responsible for the integration of SW components to switch operating system.

Define, develop and design a process for integration and customer issues.

lead customer success activities, including feature development and customer engagement.

Work with a continuous integration system, regression tools.

Be responsible for NVIDIA NVL, IB Customer engagement with R&D.

Innovate! Bring NVIDIA's networking products to shine in customer's view.

We are looking for a Principal Engineer to lead the architectural vision of the platforms core. In this role, you will be the internal technical authority responsible for building a unified, high-performance engine that processes massive telemetry streams and runs advanced predictive models, regardless of where the infrastructure resides.

What youll be doing:
Unified Architectural Vision: Lead the design of a flexible, high-scale architecture that supports both multi-tenant SaaS environments and complex on-premises deployments.
Operationalizing Predictive Models: Bridge the gap between AI research and production by architecting the framework that runs sophisticated predictive algorithms at scale, ensuring they are robust enough for mission-critical environments.
High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.
Cross-Organizational Leadership: Collaborate with networking and infrastructure teams to define the technical standards that enable the AIOps platform to integrate seamlessly with global AI infrastructure.
Technical Excellence: Drive the engineering roadmap, mentor senior staff, and serve as the final authority on architectural decisions, ensuring the platform meets the highest standards of reliability and scalability.