Jobs / United States / Nvidia Corporation
Senior Manager, Kubernetes Runtime Engineering
Nvidia Corporation · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 394 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Nvidia Corporation paid sponsored hires in similar roles113 certified filings for “Manager Systems Software” (Architectural and Engineering Managers) in CA: $214k–$248k, median $222k. Most were filed at wage level II (40%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Nvidia Corporation
The US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 394 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Nvidia Corporation →
About the role
The NVIDIA Kubernetes Engine (NKE) team is looking for a technical leader to lead the Runtime Engineering team responsible for the full configuration lifecycle of NKE tenant workload clusters. This team is responsible for software components that keep GPU workloads reliable and secure at scale. Their scope includes cluster bootstrapping, node configuration, and the container execution environment, including NVIDIA's AI Container Runtime (AICR). You will work across networking, storage, GPU resource management, and cluster security to deliver a production-grade, multi-tenant Kubernetes platform. Your team's decisions directly shape the runtime foundation that internal and external customers depend on. What You'll Be Doing: • Be responsible for the build, implementation, and operational reliability of cluster configurations for NKE tenant workloads across all supported topologies • Manage a team of engineers coordinating the entire container runtime stack: AICR, GPU management operator, DCGM, and related node-level components • Drive architecture decisions for cluster networking (CNI), storage (CSI), cluster HA , and GPU resource partitioning (MIG, MPS, time-slicing) • Define and implement cluster hardening standards, RBAC models, pod security policies, and multi-tenancy isolation boundaries • Partner with NKE platform, infrastructure, and cybersecurity teams to integrate new capabilities and resolve cross-cutting runtime concerns • Build and maintain tooling for AICR lifecycle management — provisioning, upgrades, configuration drift detection, and remediation • Represent the runtime team in architecture reviews, roadmap planning, and customer communications with NVIDIA leadership • Contribute to open source communities anywhere NKE has upstream dependencies or influence What We Need to See: • BS/MS degree in Computer Science or related field (or equivalent experience) • 12+ overall years of relevant experience designing and delivering large-scale distributed software systems, including 5+ years of people-management experience leading, developing, and scaling high-performing software engineering teams responsible for complex, production-critical software. • Experience leading a group of engineers with varying specializations and seniority levels — bridging runtime, networking, and security fields is a core part of this role • Kubernetes internals knowledge — not just usage; you understand how the scheduler, kubelet, API server, and admission controllers interact • Cluster lifecycle management experience — Cluster API, kubeadm, or equivalent; experience leading fleet-scale cluster provisioning and upgrades • Security and compliance posture — CIS Kubernetes Benchmark, pod security admission, image signing, supply chain integrity • Proven ability to design and implement maintainable APIs for consumers • Familiarity with Identity and Access Management approaches • Excel in managing up, down, and across organizations • Demonstrated ability to reach cross-organization consensus without all the details Ways to Stand Out from the crowd: • Prior experience with NVIDIA GPU Operator, DCGM Exporter, or NVLink-aware scheduling • Experience running Kubernetes at hyperscale with GPU node pools • Track record of upstream open source contributions in the Kubernetes or any open source runtime ecosystem • Experienced, persuasive, and effective interpersonal skills — written, verbal, and in front of engineering leadership • Demonstrated skills in coaching, analysis, problem solving, and short/long-term technical planning NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and