דרושים Router Testing Tech Lead ב-אנבידיה ב-ארהב

What you’ll be doing:

• Develop methods, execute performance tests, and analyze data for IC components and board-level product certifications.

• Participate in research and development of novel IC qualification processes.

• Review and interpret equipment manuals, schematics, and technical documents to support equipment setup, calibration, and installation.

• Assist engineers with analysis tasks, including equipment setup, sample preparation, basic thermal/power characterization, and troubleshooting of test equipment.

• Support reliability lab operations by contributing to test requirement assessments, metrology design/optimization, and mechanical fixture assembly/debug.

• Prepare and deliver project updates and lessons learned to the team.

What we need to see:

• Currently pursuing a masters degree in Materials Science, Mechanical Engineering, or a related field.

• Knowledge with IC packaging, reliability testing, and semiconductor technologies.

• Knowledge withpackaging/test/failureanalysis lab equipment is a plus.

• Knowledge of CAD/SolidWorks or similar design software is desirable.

• Strong problem-solving skills, attention to detail, and ability to work both independently and collaboratively.

• Excellent communication skills, with the ability to document and present technical findings clearly.

Ways to stand out from the crowd:

• Knowledge in IC packaging and physics of failure

• Experience in high power testing, such as Hipot, SIR, ECM

• Experience in image processing

You will also be eligible for Intern

What you’ll be doing:

• Participate in an international team of software engineers working on products for testing NVIDIA products.

• Oversee the design, implementation, and maintenance of scalable test automation frameworks.

• Manage, mentor, and guide a team of automation engineers.

• Design and implement robust, maintainable, and efficient automation test suite.

• Work with Continuous integration systems and regression tools, automate builds, and test suites, generate test reports, isolate and classify failures and review new degradation.

• Promote a culture of innovation, quality, and accountability. Bring SONiC NOS to shine in customer's view.

What we need to see:

• B.Sc. degree or equivalent experience in Engineering/Computer Science/related field.

• 8+ overall years of experience in software development and testing. 2+ years of experience in a leadership role.

• Proven experience in a leadership role, with a track record of successfully leading scrums and projects.

• Intrinsically motivated with a desire for automation programming.

• Strong programming skills in Python.

• Strong technical abilities, problem-solving skills, coding, and design skills.

• Ability to lead feature development, take full ownership and deliver independently.

• Linux knowledge: have a general understanding of Linux operation system concepts.

Ways to stand out from the crowd:

• Strong communication and interpersonal skills, with the ability to motivate and inspire others.

• Knowledge in one or more Networking areas: Ethernet, VLANs, TCP/UDP/IP, QoS, L2-L3 protocols.

• Extensive experience with automation frameworks (e.g., Selenium, Robot Framework, PyTest) and scripting languages (e.g., Python, Java).

What you'll be doing:

• Design, develop, and implement agentic AI blueprints (applications) that show enterprises how to utilize and deploy this technology.

• Lead technical reviews and provide mentorship, guiding the engineering team in building production-grade workflows and extending core GenAI SDK capabilities.

• Develop proof-of-concept workflows rooted in first principles that apply modern data science techniques to GenAI use cases.

• Collaborate cross-functionally with product, research, and infrastructure teams to evolve NVIDIA's agentic ecosystem, including integrations between the NeMo Agent Toolkit and other NVIDIA products and services such as the NeMo Framework, NIMs, and NVIDIA Blueprints.

• Drive performance optimization for agentic applications across the data center, focusing on improving accuracy, reducing latency, and growing efficiency.

• Establish engineering standards and best practices for developing, testing, and deploying agentic AI applications across distributed environments.

What we need to see:

• BS in Computer Engineering, Computer Science, Data Science, or a related field, or equivalent experience; MS or PhD preferred

• 8+ years of software engineering experience, including 2+ years as tech lead.

• Proficient in Python, with at least 6+ years of experience building Python libraries or applications for enterprise customers.

• Experience with GenAI application development using LLM frameworks (e.g., Langchain, Llamaindex, or AutoGen), evaluation systems (e.g., RAGAs), and observability platforms (e.g., Arize Phoenix, W&B Weave, or LangSmith).

• Experience using and understanding of agentic frameworks.

• Proficient in distributed orchestration and communication frameworks (e.g., Kafka, Ray).

• Ability to quickly learn and apply new technologies and libraries.

• Self-starter with a proactive work ethic, capable of working independently and successfully within a distributed team.

• Excellent communication and collaboration skills across distributed, cross-functional teams.

Ways to stand out from the crowd:

• Demonstrated leadership in building and scaling agentic AI applications in production.

• Experience developing your own agents in Python or a similar language (e.g., Go).

• Concrete examples/code of how you have profiled code in the past to identify performance bottlenecks and examples of how you mitigated these.

• Experience developing for GPU platforms and familiarity with NVIDIA technologies (e.g., CUDA, TensorRT, Triton, NeMo) and LLM serving frameworks (e.g., Dynamo, vLLM, SGLang).

• Experience with RAG systems and communication protocols (e.g., MCP, A2A).

What you'll be doing:

• Drive product performance and power targets, trade-offfeatures/configurationsand provide innovative solutions to complex silicon and system level problems.

• Evaluate new market segments and use cases; translate market requirements to engineering problem statements and metrics.

• Innovate Performance, power, yield and quality optimizations and features for the world’s fastest power-shipping products in the GPU and SoC market segments spanning gaming, automotive, datacenter and DL/AI.

• Develop methodologies and requirements for multi-functional teams to drive silicon and system product features to production. Incorporate productization feedback to improve the next generation.

• Lead the team for feature requirements and schedule from architecture to silicon phase of projects.

• Work alongside system architects, designers, marketing teams, chip and board designers, software/firmware engineers, HW/SW applications engineering, process/reliability authorities, ATE engineers, sales, and silicon operations, in a fast-paced, high-energy, collaborative work environment to bring industry-defining products to market.

What we need to see:

• BS or MS in EE, CE, CS, Systems Engineering or equivalent experience.

• Proven experience of 8+ years in the area of product performance and power evaluations.

• Experience with system level features, product binning methods, optimization techniques, methods and tools for data analysis and statistics.

• Experience working on new product introduction, market analysis. Background with the market segments of gaming, automotive, datacenter is preferred.

• Deep understand of critical path analysis, power/performance analysis, process technologies, transistor/device physics.

• Familiarity with silicon bringup and validation, frequency and power characterization, product analysis and optimization; hands-on post silicon experience is a plus.

• Excellent problem solving, partnership, and interpersonal skills.

• Experience working with offshore teams is required.

• Exposure to CPU/GPU/SoC architecture and HW-SW co-design is a plus

What you will be doing:

• Build and drive the technical integration of our GenAI offerings across a focused set of ISV and CSP Platforms, collaborating closely with their Platform Architects. Define technical objectives, timelines, and product adoption strategy, aligning with each partner’s long-term business objectives.

• Hands-on design and ship methodologies, code, and reference architectures that bring RAG, LLM inference, and Multi-Agent workflows to life using NVIDIA libraries (NeMo, NIMs, Triton, Tensor-RT, etc.) as well as vLLM, LangChain, vector DBs, MCP, A2A, and related technologies, deployed across major CSP platforms such as AWS, Azure, GCP, etc.

• Own the technical product engagement. Drive regular meetings, progress tracking, adoption status, and internal reporting consistent with NVIDIA's culture. You will work closely with NVIDIA Product, Engineering, Research, Solution Architecture, and other organizations to achieve the most efficient solution.

• Develop understanding across all stages of GenAI lifecycle with depth in select areas such as Data Curation, LLM Pre-training, Finetuning such as PEFT, SFT, post-training, Reasoning, RAG, Multi-agent workflows and LLM Inference for production deployments.

• Represent Partner needs and architecture design to Product and Engineering teams. Contribute to Product roadmap by articulating insights from large-scale enterprise environments and cross-industry patterns, captured from ISV engagements.

• Develop expertise in GenAI Platform Architecture and keep up to date with the latest in the industry and NVIDIA libraries, models, and frameworks to best support the partner Platform teams.

What we need to see:

• 8+ years of proven experience in technical Product or Engineering roles in Enterprise Software, Cloud Platforms, and production deployments with a focus on building partner integrations.

• Masters or PhD in Computer Science, Electrical Engineering or equivalent experience.

• Strong background in AI/ML and Deep Learning with hands-on experience building enterprise-grade GenAI systems such as intricate RAGs, Multi-Agent architectures, and production LLM deployments.

• Experience with programming languages and libraries such as HuggingFace, LangChain, Python, PyTorch, NVIDIA NeMo, vLLM, AutoGen, TensorRT-LLM, etc. and LLM application stages such as Pre-training, Customization, Inference, Evaluation, and Benchmarking.

• Ability to swiftly research, prototype, and collaborate with multiple teams to arrive at the best technical solution for new and evolving GenAI customer scenarios driving to completion, demonstrating teamwork and ownership of large projects.

• Strong understanding of enterprise deployments including MLOps, Cloud Native technologies such as Kubernetes, Docker, Kubeflow, and Enterprise IT environments including Security, Compliance, Governance, Data infrastructure, and Deployments across on-prem, hybrid, and multi-cloud platforms.

• Strong executive-caliber communication, and deep curiosity for emerging AI technologies. High ownership and initiative, keeping internal and external collaborators aligned.

Ways to stand out from the crowd:

• Track record of influencing sophisticated product decisions through trusted partner relationships, showing empathy for customer needs and an instinct for translating those into scalable platform improvements.

• Demonstrated agility in high-stakes environments required to deliver successful outcomes with partner collaborations especially with high-velocity GenAI landscape.

• Strong growth and solution outlook, highly collaborative standout colleague, able to build deep trust with engineers, executives, and multi-functional teams at both NVIDIA and Partner organizations.

What you’ll be doing:

• Participate in an international team of software engineers working on products for testing NVIDIA products.

• Oversee the design, implementation, and maintenance of scalable test automation frameworks.

• Manage, mentor, and guide a team of automation engineers.

• Design and implement robust, maintainable, and efficient automation test suite.

• Work with Continuous integration systems and regression tools, automate builds, and test suites, generate test reports, isolate and classify failures and review new degradation.

• Promote a culture of innovation, quality, and accountability. Bring SONiC NOS to shine in customer's view.

What we need to see:

• B.Sc. degree or equivalent experience in Engineering/Computer Science/related field.

• 8+ overall years of experience in software development and testing. 2+ years of experience in a leadership role, managing or software development teams.

• Proven experience in a leadership role, with a track record of successfully leading scrums and projects.

• Intrinsically motivated with a desire for automation programming.

• Strong programming skills in Python.

• Strong technical abilities, problem-solving skills, coding, and design skills.

• Ability to lead feature development, take full ownership and deliver independently.

• Linux knowledge: have a general understanding of Linux operation system concepts.

Ways to stand out from the crowd:

• Strong communication and interpersonal skills, with the ability to motivate and inspire others.

• Knowledge in one or more Networking areas: Ethernet, VLANs, TCP/UDP/IP, QoS, L2-L3 protocols.

• Extensive experience with automation frameworks (e.g., Selenium, Robot Framework, PyTest) and scripting languages (e.g., Python, Java).

W​hat You Will Be Doing:

• Lead Technical Engagement: Engage with senior technical leaders and research teams at AI model builders. Optimize their workflows by leveraging NVIDIA's complete stack for their end-to-end generative AI workflows. Serve as a primary technical point of contact.

• Drive Integration: Accelerate the technical integration of NVIDIA's core generative AI technologies. This includes NVIDIA GPU architectures, DGX systems, high-performance networking (InfiniBand), CUDA-X libraries, NeMo frameworks, and inference libraries like TensorRT. Integrate these into the training and inference pipelines of large model builders.

• Strengthen Partnerships: Support and strengthen technical implementation plans with partner AI engineering and researchers. Define clear technical objectives, performance breakthroughs, and timelines. Align these with their long-term model development goals and NVIDIA's AI strategy.

• Influence Product Roadmaps: Represent the software needs of large model builders to internal NVIDIA product and engineering teams. Contribute to product roadmap decisions by synthesizing findings from large-scale model training and inference environments. Identify cross-industry patterns and advocate for improvements to NVIDIA's core technologies.

• Maintain Strategic Relationships: Conduct regular cadence meetings. Document insights, track progress, and provide consistent internal reporting on the adoption and impact of NVIDIA technologies.

• Showcase Best Practices: Share standard methodologies for crafting and optimizing highly scalable generative AI model development pipelines across all stages. Focus on the context of large model development.

• Stay Updated: Keep current with the latest NVIDIA hardware, libraries, and system updates. Proactively share relevant insights and optimizations with partner model development teams.

What We Need To See:

• B.S. degree or equivalent experience.

• 7+ years of experience in technical product or engineering roles. Focus areas include AI/ML, high-performance computing, or distributed systems. Emphasis on core technology integration and partner collaborations is key.

• Extensive experience working with or developing platforms that facilitate large-scale AI/ML training and inference workloads. This includes distributed systems, data infrastructure, and groundbreaking GPU cluster technologies.

• Hands-on knowledge of large model architectures (e.g., Transformers, Diffusion Models). Familiarity with core deep learning frameworks (e.g., PyTorch, JAX), and NVIDIA AI acceleration libraries (e.g., CUDA, cuDNN, NCCL, TensorRT, NeMo). Understand techniques for model customization, distributed training, and inference orchestration.

• Strong understanding of compute infrastructure environments. This includes GPU cluster management, high-speed networking, parallel file systems, and deployment across on-premise and cloud infrastructures. Possess specific understanding of how large model builders operate at scale.

• Proven ability to communicate and influence senior leadership across engineering and research leaders at partner organizations. Link NVIDIA technology capabilities to crucial AI model development and business value.

• Successfully navigated fast-paced environments, taking decisive action to achieve results. Especially valuable in AI research collaborations.

• Skilled at connecting with engineers, researchers, executives, and multi-functional teams.

Ways to Stand Out From The Crowd:

• Hands-on experience with large language models (LLMs), diffusion models, distributed training frameworks, and advanced optimization techniques. Ability to prototype quickly and integrate into model development pipelines.

• Influence complex product and research decisions by nurturing positive relationships and understanding model builder needs.

• Eager drive, strategic curiosity. Anticipate market trends in AI, shape NVIDIA's roadmap, and champion innovation. Understand the large model builder landscape.

• Act as a technical advocate for NVIDIA GPU systems and software stack within assigned large model builder partners. Showcase its technical capabilities and strong value proposition.

• Understanding of large-scale system performance optimization, container orchestration (e.g., Kubernetes), and Cloud Native technologies for AI workloads.