
10,000+ employees
Founded 1993
🤖 Artificial Intelligence
🎮 Gaming
Artificial Intelligence • Gaming • Automotive
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
🕒 May 19
🏄 California – Remote
💵 $272k - $431.3k / year
⏰ Full Time
🔴 Lead
🏭 Production Engineer
🦅 H1B Visa Sponsor
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10,000+ employees
Founded 1993
🤖 Artificial Intelligence
🎮 Gaming
Artificial Intelligence • Gaming • Automotive
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
• Define and execute the technical strategy for DGX Cloud cluster operations, building the automation, GitOps, and Day 2 reliability needed to operate large-scale GPU clusters across NVIDIA Cloud Partners (NCPs) and on-prem environments • Lead design and implementation of systems for cluster lifecycle, validation, repair, upgrades, observability, and readiness • Establish patterns for Kubernetes-based GPU cluster operations across partner and on-prem environments • Identify and eliminate operational toil through software, APIs, automation, and agent-assisted workflows • Set technical standards for production readiness, SLOs, incident response, handoff gates, and operational acceptance • Mentor engineers and influence platform, infrastructure, storage, networking, security, and workload teams
• 15+ years of experience building and operating large-scale distributed systems or cloud infrastructure • Deep experience with Kubernetes, Linux, infrastructure automation, and production operations • Strong programming experience in Go, Python, or similar • Proven ability to lead complex cross-org technical initiatives • Experience designing reliable systems with clear SLOs, observability, incident response, and automation • BS/MS in Computer Science or equivalent experience.
• equity • benefits
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