The job in two lines
This role involves managing the integration and deployment of large-scale AI supercomputing systems in datacenters, collaborating with engineering teams to build and deploy GPU computing systems, and ensuring the successful integration of new AI clusters with datacenter facilities.
Summary by Rezifi's AI, from NVIDIA’s posting. Years and pay appear only when the posting states them.
What you'd do
- Collaborate with engineers to build and deploy large-scale GPU computing systems
- Lead the integration of new AI clusters with datacenter facilities
- Coordinate design and fit-out of new datacenter builds
- Own and produce detailed documentation for the end-to-end process for datacenter fit-out and integration
- Communicate internally with engineering leadership to prioritize and address key issues
Skills it is built around
- high-performance computing systems
- GPU clusters
- Data Center Architecture
Required
- power
- cooling
- Instrumentation
Nice to have
- Prometheus
- grafana
- Splunk
- Modbus
- BACnet
The facts
- Experience
- 8+ years
- From the posting: “8+ years of overall experience”
- Pay
- $168,000 to $322,000 a year
- NVIDIA’s own figure.
- Level
- Senior
- Field
- Datacenter engineering
The full posting
From NVIDIA’s careers site
As NVIDIA posted it. See the original
NVIDIA is looking for a highly-motivated Technical Program Manager (TPM) to join our Applied Systems Engineering Team to drive datacenter integration for the next generation of NVIDIA AI supercomputing systems. This TPM will play a crucial role throughout the lifecycle of the latest AI systems at scale, from datacenter design and requirements definition, through systems integration of AI clusters into the datacenter environment, and support for these systems as they enter production.
This role will drive collaboration between engineering leaders across multiple hardware and software teams, helping us work together to build AI supercomputers for NVIDIA engineers and develop reference architectures to advise customers and partners.
What you’ll be doing:
Collaborate with outstanding engineers and architects to 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 with demanding requirements on power, cooling, and instrumentation
Coordinate design and fit-out of new datacenter builds, working with both internal engineering teams and external contractors
Own and produce detailed documentation for the end-to-end process for datacenter fit-out and integration
Communicate internally with engineering leadership to prioritize and address key issues essential to the success of our largest customers
What we need to see:
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
A passion for understanding challenging technical problems and driving the process of finding a solution
Strong teamwork and interpersonal skills, to facilitate building a collaborative workflow for coordination between many teams
Ways to stand out from the crowd:
Understanding of datacenter design, including familiarity with power and cooling technologies
Expertise in system monitoring and instrumentation of large clusters, using technologies such as Prometheus, Grafana, Splunk, Modbus, and BACNet
Experience working with the engineering or academic research community supporting high-performance computing or deep learning
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 18, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.More like this
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