Used Tools & Technologies
HPCRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Grafana @ 3
Prometheus @ 3
Leadership @ 3
Splunk @ 3
GPU @ 3
Deep Learning @ 3
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
Responsibilities
- 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.
Requirements
- 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 (Preferred)
- 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.
Compensation & Other Details
- Base salary range: 168,000 USD - 258,750 USD (final base salary determined by location, experience, and pay of employees in similar positions).
- Eligible for equity and benefits (see NVIDIA benefits page).
- Applications accepted at least until April 20, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.