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NVIDIA
NVIDIA
H1B Visa SponsorArtificial IntelligenceHealthcareManufacturing
NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.
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Senior Software Engineer, Distributed Systems and EDA Infrastructure

Build dependable automation and platform services for NVIDIA’s electronic design automation infrastructure. Operate large GPU and CPU compute fleets through scheduling, monitoring, diagnostics, and recovery systems.

USUnited StatesCACaliforniaMAMassachusettsNCNorth CarolinaTXTexasWAWashington
$152,000 – $287,500 / year
HybridFull-timeSeniorEnglish RequiredBlockchain Engineer
Distributed SystemsGoKubernetesLinuxNode.jsPython

Description

  • Create platforms that automate provisioning, configuration, operations, and lifecycle management for large-scale GPU and CPU compute infrastructure
  • Develop monitoring, system-health, and remediation capabilities that strengthen the reliability, availability, and utilization of EDA compute environments
  • Automate hardware deployment, operating-system setup, firmware and software updates, cluster registration, and recovery procedures
  • Build dependable services and workflows that connect workload schedulers with infrastructure-management and observability platforms
  • Analyze hardware diagnostics, operating-system signals, scheduler information, and network and storage telemetry to diagnose failures and restore unhealthy systems
  • Partner with EDA, infrastructure, networking, storage, and hardware engineering teams to deliver scalable platforms for critical chip-design workloads
  • Contribute to incident response, root-cause investigations, capacity planning, and ongoing improvements to production services

Requirements

  • At least five years of software or infrastructure engineering experience supporting large-scale production systems
  • Bachelor’s degree in computer science, engineering, physics, mathematics, or a related discipline, or equivalent practical experience
  • Strong programming ability in Go or Python
  • Solid command of data structures, algorithms, testing, and software design principles
  • Experience creating automation for distributed systems and extensive Linux-based compute fleets
  • Understanding of performance, security, reliability, fault tolerance, state management, and data consistency in complex systems
  • Experience with infrastructure automation, software delivery, observability, and operational recovery
  • Clear communication skills and the ability to collaborate across teams, organizations, and geographic regions
  • Experience with large-scale EDA or high-performance computing infrastructure is advantageous
  • In-depth knowledge of Linux, GPU and CPU server architecture, networking, storage, and bare-metal lifecycle management is advantageous
  • Hands-on experience with Slurm, LSF, Kubernetes, or Bright Cluster Manager is advantageous
  • Experience supporting EDA applications, license-management platforms, high-throughput batch workloads, or semiconductor design processes is advantageous
  • Experience developing automated health checks, break-fix remediation, firmware and operating-system upgrade processes, or node-provisioning systems is advantageous
  • Experience operating infrastructure across multiple data centers or varied hardware environments is advantageous

Benefits

  • Equity
  • Benefits

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