below marketmost similar roles pay hereabove market
This role pays more than
54%
of similar roles. Most pay
$181,968–$244,875
— the blue band above.
At the midpoint, this role pays about
$213k
versus about
$213k
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
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
The Senior Datacenter Technical Program Manager, At-Scale AI Clusters joins the Applied Systems Engineering Team to drive datacenter integration for next-generation AI supercomputing systems. This role involves managing the full lifecycle of AI systems, including datacenter design, requirements definition, and systems integration into production environments. You will collaborate with hardware and software engineering leaders to build large-scale GPU computing systems based on reference supercomputing architectures. Key responsibilities include coordinating datacenter fit-outs, managing power and cooling requirements, and producing end-to-end process documentation. Required skills include experience with high-performance computing systems and GPU clusters. Preferred technical expertise includes datacenter design, system monitoring, and instrumentation using tools like Prometheus, Grafana, Splunk, Modbus, and BACNet to solve complex infrastructure challenges for large-scale AI clusters.
Build and deploy large-scale GPU computing systems based on NVIDIA's reference supercomputing architectures.
Lead the integration of new AI clusters with datacenter facilities regarding power, cooling, and instrumentation.
Coordinate the design and fit-out of new datacenter builds with internal teams and external contractors.
Produce detailed documentation for the end-to-end process of datacenter fit-out and integration.
Communicate with engineering leadership to prioritize and address key issues for major customers.
Develop reference architectures to advise customers and partners on AI supercomputing systems.
What we're looking for
BS in Applied Science or Engineering or equivalent experience.
8+ years of overall experience.
Experience with high-performance computing systems and GPU clusters deployed in on-premises datacenters.
Strong teamwork and interpersonal skills to facilitate collaborative workflows between many teams.
Understanding of datacenter design, including familiarity with power and cooling technologies (preferred).
Expertise in system monitoring and instrumentation of large clusters using technologies such as Prometheus, Grafana, Splunk, Modbus, and BACNet (preferred).
Experience working with the engineering or academic research community supporting high-performance computing or deep learning (preferred).
Remote (Santa Clara, CA)4 days ago
$168,000–$258,750
Machine Learning
Deep Learning
GPU Technology
AI Infrastructure
Scaled Agile Framework
Hardware Bring-up
Model Optimization
Inference Frameworks
Program Tracking Tools
Production AI Software