Build and operate automation and tooling for large-scale NVIDIA GPU infrastructure. Responsibilities include bare-metal provisioning, hardware validation, firmware and software upgrades, cluster lifecycle management, BMC and Redfish integration, failure diagnosis, automated recovery, production handoff, on-call support, incident response, and root-cause analysis across hardware, networking, Linux, Kubernetes, and distributed services.
NVIDIA DGX Cloud builds and operates large-scale GPU infrastructure for AI workloads. We are looking for Software Engineers with SRE or Production Engineering experience who have worked hands-on with bare-metal NVIDIA systems. This team builds the software and operational tooling that moves GPU capacity from installed hardware to production service supporting an IaaS production environment of BMaaS, VMaaS.
What you’ll be doing:
- Build automation for bare-metal provisioning, hardware validation, firmware and software upgrades, repair, and cluster lifecycle management.
- Develop tools that interact with BMC and Redfish interfaces to monitor hardware health, manage server state, and assist recovery workflows.
- Handle and advance NVIDIA NVL72 systems and BlueField-3 or later DPUs throughout cloud partner and on-premises environments.
- Diagnose failures across servers, DPUs, GPU systems, CPU systems, networking, Linux, and Kubernetes; turn recurring issues into automated detection and repair.
- Define validation and handoff criteria so new capacity enters production safely and consistently.
- Take part in on-call duties, incident response, root-cause analysis, and follow-up to implement permanent solutions.
- Work with hardware, networking, platform, data center operations, and partner teams to resolve issues across ownership boundaries.
What we need to see:
- 12+ years building software for or operating production infrastructure, including substantial hands-on bare-metal experience.
- Strong Go or Python skills, with a record of delivering production automation and services.
- Direct experience with BMC and Redfish in server provisioning, health inspection, power management, or fault diagnosis.
- Practical experience working directly with NVIDIA GPU hardware, such as NVL72 systems, and BlueField-3 or newer DPUs.
- Experience with Linux, firmware and driver management, network boot, and the server lifecycle from initial provisioning through repair.
- Experience managing production reliability through on-call duties, incident response, observability, and durable solutions.
- Ability to debug failures across hardware, host operating systems, networking, and distributed services.
- Clear communication and demonstrated ownership of problems that span multiple teams.
- BS/MS in Computer Science or equivalent experience in a practical setting.
Ways to stand out from the crowd:
- Experience operating BlueField DPUs in DPU mode, including host-to-DPU connectivity and lifecycle debugging, with DPU or equivalent experience considered.
- Background with NVLink, InfiniBand, Spectrum-X, or GPU cluster performance validation.
- Experience building safe, repeatable workflows for rack-scale bringup, firmware upgrades, hardware replacement, and customer handoff.
- Experience with Kubernetes, GitOps, Argo CD, SLOs, and fleet-wide automation.
At NVIDIA, you’ll help make next-generation AI infrastructure production-ready at scale!
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 170,000 CAD – 220,000 CAD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
Similar Jobs
Cloud • Security • Software • Cybersecurity • Automation
Own complex enterprise customer escalations from engagement through resolution, coordinating Engineering, Support, Product, Customer Success, and Sales. Lead executive communications, maintain customer-facing resolution plans, manage commitments, coordinate with Incident Managers, and oversee post-escalation reviews and relationship repair. Develop escalation playbooks and process improvements while providing globally distributed, on-call support for high-severity customer situations.
Top Skills:
Ci/CdCloud-Native PlatformsDevsecopsGitlabPagerdutySalesforceSlackZendesk
Big Data • Fintech • Mobile • Payments • Financial Services
Build and improve high-traffic consumer web experiences using React and TypeScript. Develop experimentation, instrumentation, marketing integrations, attribution, and measurement systems while meeting privacy requirements. Collaborate with Product, Design, Marketing, Analytics, and Data Engineering, write tested and extensible code, monitor system metrics, support availability and on-call efforts, participate in code reviews, and contribute to team development.
Top Skills:
Google Tag ManagerJavaScriptReactTypescriptVue
.png){kind=logo}
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Senior Data Scientist responsible for translating product and machine learning goals into actionable data specifications. The role oversees dataset curation, filtering, processing, pipeline quality, and behavioral data integrity for production machine learning. It requires collaboration with ML engineers, product engineers, TPMs, and annotation teams, along with strong data science, mathematical, analytical, communication, and cross-functional leadership skills.
Top Skills:
ConfluenceExperiment Tracking FrameworksGitJIRAMachine LearningPythonSlackUnix Shell
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
