Distinguished Engineer – GPU Fleet Operations Automation

OperationsOperationsFull TimeRemoteTeam 10,001+Since 1993H1B SponsorCompany Site LinkedIn

Location

California + 4 more

Posted

70 days ago

Salary

$308K - $471.5K / year

Bachelor Degree15 yrs expExperience acceptedEnglishCloudKubernetes

Job Description

• Various Architectural Work: define and drive the technical implementation for DGX Cloud operations practice for GPU fleet lifecycle. • Collaborate on Cross Domain Disciplines: drive the technical strategy and awareness for best practices and technical capabilities into DGX Cloud engineering practices. • Accelerate Integration: Guide the technical delivery into DGX Cloud across all delivery environments: enterprise, public cloud, and high security, isolated, sovereign. • Engage Stakeholders: Collaborate with customers, infrastructure providers, and partners to ensure NVIDIA’s solutions set the industry standard for operational excellence. • Full Software and System Lifecycle: From ideation to architecture, design, development, deployment, operations, and full lifecycle management, lead all technical aspects of planning and continuous evolution of large technical scope.

Job Requirements

15-18+ overall years in technical roles with a focus on operations and automation for cloud infrastructure, platforms, and applications.
5-10+ years of lead experience
BS/MS or higher or equivalent experience in systems / software engineering, or related engineering fields
Technical proficiency in multi-tenant data center and cloud-native architectures, with bare metal, virtualization, containerization, and higher level abstractions (IaaS, Kubernetes, Slurm), AI/ML platforms and applications.
Shown success delivering high-impact technically complex solutions that achieve high levels of transparency into resource utilization, performance, and operational insights.
Technical Leadership: Ability to synthesize multi-functional needs into architecture and design while guiding internal execution across complementary teams.
Communication and Partnership: Strong collaboration and influence skills, capable of leading engineering engagement, presenting with peers, partners, and working with high performance accelerated computing customers.