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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in large-scale production systems, with a strong focus on GPU asset provisioning, configuration, and lifecycle management. Proficient in systems programming, Linux administration, and container orchestration, ensuring high reliability and scalability in distributed environments.
Highest-signal resume keywords
Expert Level Knowledge Of Go, Python, And/or RustDeep Knowledge Of Kubernetes And/or SLURMExtensive Expertise In Datacenter Operations And GPU HardwareStrong Background In Linux System AdministrationExperience Managing Large-Scale Distributed Systems
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 ProgrammingData StructuresAlgorithmsLinux AdministrationContainer OrchestrationDistributed Systems ManagementCluster ManagementGPU Asset ManagementRDMA NetworkingData Synchronization
Certifications & Qualifications
BS In Computer ScienceBS In EngineeringBS In PhysicsBS In Mathematics
Industry Keywords
Machine Learning SystemsData Center ManagementMonitoring And Health ManagementFault ToleranceState ManagementPerformance And SecurityCloud ProvidersTelemetry
Tech Stack
Tools & technologiesCloudDistributed SystemsKubernetesLinuxPythonRustGo
About the role
Key responsibilities & impact- Contribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers
- Build end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems
- Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets
- Harness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry
- Build automated test infrastructure used to qualify distributed systems for operation
- Partner with engineering teams across NVIDIA to ensure software integrates seamlessly from hardware through AI training applications
Requirements
What you’ll need- 12+ years of experience in a similar role working 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, and/or Rust)
- Solid understanding of Data Structures and Algorithms
- Strong background in Linux system administration and management
- Deep knowledge of container orchestration platforms such as Kubernetes and/or SLURM
- Understanding of performance, security, and reliability in complex distributed systems
- Familiarity with system level architecture, data synchronization, fault tolerance, and state management
- Proficiency in designing and building widespread distributed networks
- Experience managing large-scale distributed systems independently of cloud providers
- Extensive expertise in datacenter operations and GPU hardware
- Hands-on experience working with RDMA networking
- Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, SLURM)
Benefits
Comp & perks- Equity
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