FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Senior GPU and HPC Infrastructure Engineer – DGX Cloud
NVIDIASenior GPU and HPC Infrastructure Engineer at NVIDIA scaling its AI Infrastructure with expertise in software engineering and systems programming.
Posted 7/7/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $184,000 - $356,500 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expert-level knowledge in systems programming languages such as Go and Python, along with extensive experience in Linux system administration and management. Proficient in building automated solutions for large-scale Machine Learning systems and managing GPU asset provisioning and lifecycle management across cloud environments.
Highest-signal resume keywords
Expert Level Knowledge Of GoExpert Level Knowledge Of PythonLinux System AdministrationCluster Management Systems (Kubernetes, SLURM)Large-Scale Production Systems Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Systems ProgrammingAutomationGPU Asset ProvisioningLifecycle ManagementMonitoring And Health ManagementData SynchronizationFault ToleranceState ManagementPerformance SecurityReliability In Distributed Systems
Certifications & Qualifications
BS In Computer ScienceBS In EngineeringBS In PhysicsBS In Mathematics
Industry Keywords
Machine LearningCloud ProvidersDatacenter OperationsNVLINK TopographyDistributed Systems
Tech Stack
Tools & technologiesCloudDistributed SystemsGoKubernetesLinuxPython
About the role
Key responsibilities & impact- Contribute to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers
- Build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems
- Implement monitoring and health management capabilities that enable reliability, availability, and scalability of GPU assets
- Manage NVLINK topography across GPU clusters
- Build automated test infrastructure to qualify distributed systems for operation
- Collaborate with engineering teams to ensure software integration from hardware to AI training applications
Requirements
What you’ll need- 10+ years of software engineering experience on large-scale production systems
- BS in Computer Science/Engineering/Physics/Mathematics or other comparable Degree or equivalent experience
- Expert level knowledge of a systems programming language (Go, Python)
- Expert level knowledge of Linux system administration and management
- Understanding of cluster management systems (Kubernetes, SLURM)
- Understanding of performance, security and reliability in complex distributed systems
- Familiarity with system level architecture, data synchronization, fault tolerance and state management
Benefits
Comp & perks- Eligible for equity and benefits