Senior AI Compute Scheduler (GPU) – Slurm & Kubernetes

NVIDIA Corporation; Durham (NC); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Durham, NC seeks an experienced Scheduler/Platform Engineer to design, build, and operate scheduling systems for large GPU fleets using Slurm and Kubernetes. You will implement queueing, placement, quotas, preemption, reservations, and batch workloads to improve GPU utilization and reliability.

Requires a degree in CS/CE/EE or related field plus 6+ years in production systems; strong Go/C/C++, Python, Kubernetes, and Linux expertise are essential.

Qualifications

• Requires a bachelor's or master's degree in computer science, computer engineering, electrical engineering, or related field, or equivalent experience.

Responsibilities

• Design, build, and operate scheduling systems for large GPU fleets using Slurm and Kubernetes.
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• estimated_low
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• estimated_high
• currency
• frequency
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• tax
• application_email
• job_end_date
• contact_person
• hiring_department_name
• CoT_job_summary_short
• job_summary_short
• contract_type
• location_type
• remote_scope
• perks
• stated_min
• stated_max
• stated_absolute
• salary_estimation_cot
• estimated_low
• estimated_medium
• estimated_high
• currency
• frequency
• bonus
• tax
• application_email
• job_end_date
• contact_person
• hiring_department_name

Skills

Slurm

Kubernetes

Go

C

C++

Python

Batch Scheduling

Cluster Scheduling

Kubernetes Controllers and Operators

Custom Resource Definitions

Linux Systems

Containers

Cgroups

GPU Scheduling

Topology-Aware Placement

Production Reliability

Education

Bachelor's or Master's degree in CS/CE/EE or related field

Tools

Kubernetes

Go

C

C++

Python

Linux

Job description

NVIDIA Corporation in Durham, NC seeks an experienced Scheduler/Platform Engineer to design, build, and operate scheduling systems for large GPU fleets using Slurm and Kubernetes. You will implement queueing, placement, quotas, preemption, reservations, and batch workloads to improve GPU utilization and reliability.

Requires a degree in CS/CE/EE or related field plus 6+ years in production systems; strong Go/C/C++, Python, Kubernetes, and Linux expertise are essential.