22 days ago
Ra‘ananna, IsraelSenior
Responsibilities
- Define architectures for management and intelligent automation capabilities across telemetry, observability, remediation, and operational automation.
- Engage customers, cluster operations teams, and compute authorities to architect solutions that improve operational efficiency, reliability, and scalability.
- Translate architectural recommendations into prioritized Product and Engineering features, requirements, dependencies, and success criteria for inclusion in the Plan of Record.
- Resolve tradeoffs across hardware, firmware, software, and data platforms with attention to scale, reliability, performance, and usability.
- Guide implementation through hands-on proofs of concept and technical investigations.
- Provide strategic direction and system-level technical leadership across teams.
Requirements
- MSc or higher in Computer Engineering or Computer Science, or equivalent experience.
- 8+ years of experience in system or software architecture, with a record of delivering sophisticated distributed systems in production.
- Hands-on experience architecting and delivering distributed software systems, including cloud-native services, deployment, and orchestration.
- Deep understanding of data center infrastructure across compute, networking, and management systems and their interactions at scale.
- Ability to connect broad system perspectives with precise technical reasoning.
- Experience translating customer needs into system capabilities and influencing technical and product decisions.
- Strong ownership, initiative, follow-through, technical writing, and communication skills.
- Preferred experience includes AI factory infrastructure, large-scale GPU clusters, HPC, distributed AI training and inference workloads, hardware/software co-design, telemetry and observability platforms using AI/ML, LLM agent development, and open-source contributions.
Benefits
- Competitive salaries and a generous benefits package.
- Engineering role focused on large-scale AI Factories, intelligent systems, and AIOps.
- Work with forward-thinking engineering teams at NVIDIA; specific work arrangement and other practical logistics are not stated.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.