This role pays less than
56%
of similar roles. Most pay
$177,250–$235,750
— the shaded band above.
At the midpoint, this role pays about
$197k
versus about
$206k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Senior GPU Supercomputer Scheduler Engineer on the Managed AI Research Superclusters team, you will design and develop new scheduling features and add-on services to improve GPU compute clusters across dimensions like resource usage fairness, occupancy, waste, resilience, performance, and power usage. You will build batch workload management and orchestration services while providing support to resolve scheduler issues for demanding deep learning and high-performance computing workloads. The role involves performing performance analysis of deep learning workflows, developing large-scale automation solutions, and conducting root cause analysis. Key technical requirements include proficiency in C/C++, Go, Python, and bash, along with experience in Linux environments, container technologies like Docker, Singularity, or Podman. You will also utilize knowledge of SLURM or K8s batch schedulers to manage complex multi-node GPU workloads and system co-design challenges.
C
C++
CUDA
Kernel Mode Development
Linux
Parallel Computing
System Software
Device Drivers
Virtual Memory
Interconnects
Memory Hierarchy
Interrupts
Memory-Mapped IO