7 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Design and build platforms for provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure.
- Develop monitoring, health-management, and remediation systems to improve reliability, availability, and utilization of EDA compute environments.
- Automate hardware deployment, operating-system configuration, firmware and software updates, cluster enrollment, and recovery workflows.
- Build services and workflows integrating workload schedulers, infrastructure management systems, and observability platforms.
- Use hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify failures and restore unhealthy systems.
- Collaborate with EDA, infrastructure, networking, storage, and hardware engineering teams on scalable solutions.
- Participate in incident response, root-cause analysis, capacity planning, and continuous production-service improvement.
Requirements
- 5+ years of software engineering or infrastructure engineering experience supporting large-scale production systems.
- BS in Computer Science, Engineering, Physics, Mathematics, or a related field, or equivalent experience.
- Strong programming experience in Go or Python with knowledge of data structures, algorithms, testing, and software design.
- Experience designing distributed-systems automation for large fleets of Linux-based compute nodes.
- Understanding of performance, security, reliability, fault tolerance, state management, and data consistency.
- Experience with infrastructure automation, software deployment, observability, and operational recovery.
- Strong communication, cross-functional collaboration, and systematic problem-solving skills.
- Preferred experience with large-scale EDA or high-performance computing infrastructure, Linux, GPU and CPU server architecture, networking, storage, and bare-metal lifecycle management.
- Preferred experience with Slurm, LSF, Kubernetes, Bright Cluster Manager, EDA applications, license-management systems, high-throughput batch workloads, or semiconductor design workflows.
- Preferred experience building automated health checks, break-fix remediation, firmware and operating-system upgrade workflows, node-provisioning systems, and infrastructure across multiple data centers or heterogeneous hardware environments.
Benefits
- Base salary is listed for Level 3 and Level 4; employees are also eligible for equity and benefits.
- Applications will be accepted at least until October 19, 2026.
- This posting is for an existing vacancy.
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.