NVIDIA is looking for a Systems & Software Engineer interested in building and running reliable large scale infrastructure platform services. In this role you will create and support automation that manages infrastructure, as part of our organization running EDA platforms atop of NVIDIA hardware. What you’ll be doing: Design, build, deploy, and run infrastructure services & manage the software life cycle in scope to meet our business goals Build and maintain automation to eliminate manual toil and scale output without scaling effort Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation Consult with and provide consultation for peer teams on systems design best practices What we need to see: BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience Experience coding in Python and/or Go. Note : you must be able to produce code without AI assistance during the interview process. Experience with infrastructure automation and distributed systems design Experience developing tools for running large scale private or public cloud systems in production In depth knowledge of Linux systems and Containers A track record showing a good balance between initiating your own projects, convincing others to collaborate with you and collaborating well on projects initiated by others. <

Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure NVIDIA is hiring engineers to build and scale the infrastructure that supports our Electronic Design Automation (EDA) workloads. We are looking for engineers with strong programming skills, a deep understanding of distributed systems, experience operating large-scale production infrastructure, and excellent communication and planning abilities. You will help design reliable automation and platform services that manage large fleets of GPU-based and CPU-based compute systems used by engineering teams across NVIDIA. The ideal candidate is comfortable working across software, operating systems, cluster schedulers, networking, storage, and physical hardware. You should enjoy solving complex operational problems, eliminating repetitive work through automation, and building systems that remain reliable as infrastructure grows. If you are creative, pragmatic, and motivated to improve how critical engineering workloads are delivered, we would like to hear from you. What You Will Be Doing: Design and build platforms that automate the provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure. Develop monitoring, health-management, and remediation systems that improve the reliability, availability, and utilization of EDA compute environments. Automate hardware deployment, operating-system configuration, firmware and software updates, cluster enrollment, and recovery workflows. Build reliable services and workflows that integrate with workload schedulers, infrastructure management systems, and observability platforms. Use hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable &#34;flight recorder&#34; for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as &#34;Hardware Fault,&#34; &#34;Software Bug,&#34; or &#34;Environment Issue.&#34; This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define &#34;signals of impending failure,&#34; enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6&#43; years in systems programming. Experience building automated

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Operating a vehicle remotely over cellular networks is challenging and critical. You will be responsible for ensuring that our "eyes on the road" never blink. You’ll tackle deep-stack networking challenges—from bonding multiple LTE carriers to designing custom FEC (Forward Error Correction) algorithms that out-perform standard protocols. About the Work Engineered Connectivity: Architect a network bonding framework to aggregate bandwidth across multiple cellular providers (Verizon, AT&T, T-Mobile) to ensure zero-drop connectivity. Performance Modeling: Build sophisticated ns-3-like simulations to "stress test" our stack against edge cases like tunnel entries, rural dead zones, and network congestion. Optimization: Develop and implement custom congestion control algorithms specifically tuned for high-bitrate, low-latency video streaming. Cross-Functional Leadership: Partner with Hardware and Embedded teams to optimize the netw

Job Details: Job Description: The Role and Impact Join Intel's Design Technology Platform (DTP) organization and become an integral part of a highly skilled team driving the development of cutting-edge technologies. As an EDA Tools Software Engineer, you will design, develop, test, and debug software tools and methodologies that directly support Intel's hardware product design and manufacturing processes. Your work will enable design teams to innovate faster, meet complex manufacturability constraints, and deliver industry-leading products to market. By contributing to Intel's advanced process technologies, you will play a pivotal role in achieving leadership in design automation and fostering a culture of innovation. Key Responsibilities Design, develop, and debug Fill components of Process Design Kits (PDKs), Provide algorithmic solutions using tools such as Calibre, ICV, and Pegasus to address density deficiencies and ensure manufacturability compliance. Collaborate with process developers, design rule owners, and end users to define requirements and implement state-of-the-art solutions. Automate workflows to enhance efficiency, accuracy, and deployment across design teams. Develop comprehensive test cases and systems to validate software tools and ensure seamless integration with various design methodologies. Innovate and drive advancements in EDA tools and methodologies to meet the evolving needs of Intel's technology ecosystem. Partner with cross-functional teams and external EDA vendors to define and implement new tool features and methodologies. Maintain documentation, including training materials and user guides, to support customers and ensure robust deployment.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. In this position, you will be joining a brilliant team to collaborate with Micron’s various design and verification teams all over the world, support the efforts of design verification flow development, optimization, and implementation and work with cross-functional team to assure the best cost, quality, reliability, time-to-market, and customer satisfaction We are seeking a talented CAD senior engineer specialized in analog and digital simulations to join our high-achieving engineering team. As a CAD senior engineer, you will play a pivotal role in optimizing and simulating complex analog and digital circuits, contributing to the development of state-of-the-art products that shape our industry. You will get a chance to develop the industry's first and unique flows to enhance productivity and reduce pre-silicon failures. Responsibilities: Work closely with memory design teams and solve their daily challenges and provide complete solutions for the future. Proactively identify problem areas for improvement, propose, and develop innovative solutions. Develop highly scalable, and clean software systems. Continuously evaluate and implement new tools and technologies to improve the current software flows. Work with EDA vendors to evaluate and integrate E