Leads engineering teams developing platform software for GPU-accelerated applications using Kubernetes, container runtimes, Kata Containers, and Confidential Containers. Responsibilities include enabling GPUs as Kubernetes resources, integrating software across NVIDIA’s technology stack, managing priorities, and delivering secure, reliable distributed systems. The role requires deep systems software expertise, engineering management experience, and hands-on knowledge of containers, Linux, cloud computing, virtualization, and confidential computing technologies.
NVIDIA is looking for a hardworking Senior Engineering Manager to effectively manage the team working on platform software based on open-source Container runtimes, Kubernetes, Kata and Confidential Container technologies. We expect you to have strong engineering management skills, a deep understanding of designing and building software, experience with Systems Software and Distributed systems, as well as excellent communication and planning skills. We also welcome out-of-the-box problem solvers who can provide new ideas while being strong at completing tasks. Expect to be constantly challenged, improving and evolving for the better. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. If you're creative, passionate about what you do, autonomous, and love having fun, we want to hear from you!
What you will be doing:
- You'll be part of a small and dynamic team that explores innovative ways to make GPU-accelerated applications easier to develop, deploy, and monitor.
- Work on enabling GPUs as first-class resources in Kubernetes, Kata Containers and Confidential Containers.
- This is an excellent opportunity to join the core group working on Cloud Native technologies enabling NVIDIA accelerators in the k8s environment.
- Work with engineering teams across all of NVIDIA to ensure your team’s software integrates seamlessly up and down the stack.
- Proficiently multitasking on different tracks to efficiently address evolving priorities.
What we need to see:
- BS/MS in Computer Science, or related field (or equivalent experience)
- A minimum of 12 years of relevant professional experience, including at least 5 years dedicated to managing high-performing engineering teams.
- Strong understanding of Container Orchestration Systems (K8s) and Container Technology.
- Working knowledge in Systems programming languages, such as Rust and Go, alongside a strong foundation in data structures and algorithm design.
- Knowledge and experience working with System internals of Unix/Unix-like kernels such as Linux.
- Strong background in Cloud Computing and Distributed Software design and development.
- Understanding of performance, security, and reliability in complex distributed systems.
Ways to stand out from the crowd:
- Strong recent experience managing engineering teams focused on Containers, Kubernetes and Confidential Computing technologies.
- Real-world strong hands-on experience with Containers and Kubernetes.
- Proficient with Kata Containers and Container sandboxing technologies
- Well-versed in Attestation concepts, Key Broker Service, etc.
- Knowledgeable with virtualization technologies, SR-IOV, vGPU, etc.
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 is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. We are looking for great people like you to help us accelerate the next wave of artificial intelligence.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.NVIDIA Santa Clara, California, USA Office
2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara
NVIDIA San Francisco, California, USA Office
San Francisco, United States
NVIDIA San Jose, California, USA Office
San Jose, United States
Similar Jobs
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Provides customer-facing cybersecurity consulting focused on threat emulation, exposure management, red teaming, vulnerability management, penetration testing, and technical risk mitigation. Uses SafeMind, Falcon, and AI-enabled capabilities to evaluate exposures, refine risk outputs, advise technical and executive audiences, improve service delivery, and mentor junior consultants. Requires advanced security assessment, infrastructure, networking, operating system, automation, and scripting expertise, with occasional travel.
Top Skills:
Agentic AiBurp SuiteCobalt StrikeFalconFirewallsGenerative AiLinuxLoad BalancersmacOSMail ServersMetasploitNessusNmapProxiesRoutersSafemindSwitchesUnixWeb ServersWindowsWireless Access Points
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Serves as an embedded technical advisor to government customers, implementing, configuring, troubleshooting, and optimizing CrowdStrike Falcon environments in FedRAMP and DoD-accredited environments. Responsibilities include threat-hunting mentorship, incident-management guidance, security-tool integrations, scripting with Falcon APIs, vulnerability and asset-management support, project coordination, technical reporting, and customer training. Requires strong cybersecurity and consulting experience, government-clearance eligibility, U.S. citizenship or permanent residency, and up to 20% travel.
Top Skills:
AcasActive DirectoryAWSAws GovcloudAzure AdAzure GovernmentBashBatchChefCitrixCrowdstrike FalconEmassFalcon ApisFedrampGoogle Assured WorkloadsGoogle Cloud PlatformGroup PolicyIbm BigfixLinuxLogscalemacOSMcafee EpoAzureMssqlNessusNist Sp 800-37PdqPowershellPsexecPuppetPythonRmfScapSccmSIEMSplunkSsoStig ViewerWindowsXacta
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Perform real-time security operations for customers by triaging, investigating, and responding to alerts across endpoint, identity, email, and cloud environments. Analyze EDR telemetry, logs, and forensic artifacts; investigate Microsoft 365 threats such as BEC and AITM attacks; communicate findings and remediation guidance; and improve detection and response processes. The role requires foundational cybersecurity knowledge, strong troubleshooting and communication skills, scripting familiarity, and willingness to work a 4x10 schedule including weekends.
Top Skills:
Active DirectoryAIBashEdrLinuxmacOSMicrosoft 365Microsoft Entra IdMitre Att&CkNg-SiemOktaPowershellPythonWindows
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
