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NVIDIA

Senior MEP Engineer – Datacenter Lab Infrastructure

NVIDIA is hiring a Senior MEP Engineer – Datacenter Lab Infrastructure in Santa Clara, United States. It pays $152k-$253k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Level classes it as a senior role.
  • NVIDIA has 2,700+ other open roles on Level.

AI in this role

We are looking for a highly motivated and experienced Senior MEP (Mechanical, Electrical, and Plumbing) Engineer to join our product engineering team, where your work will directly enable the development and deployment of next-generation datacenter products. As a key contributor within our team, you will plan and implement lab MEP infrastructure—from liquid cooling systems to telemetry, control architectures, and power distribution. This role sits at the intersection of product development and facility engineering, supporting one of the most impactful hardware organizations in the industry. If you thrive in a fast-paced, highly technical environment and want to directly influence the future of AI and accelerated computing, this is the team for you.

What you'll be doing:

Working closely with product engineering, lab operations, and facilities teams, this role drives the full lifecycle of MEP infrastructure that supports NVIDIA's showcase-ready lab environments—from early-stage planning and design through construction, commissioning, and ongoing operations. Responsibilities span a broad technical scope and require both deep domain expertise and strong multi-functional collaboration. Day-to-day work includes:

  • Owning the design, specification, and implementation of datacenter-grade power and cooling infrastructure for lab environments, including UPS systems, PDUs, switchgear, liquid cooling distribution systems, and air conditioning

  • Planning and implementing showcase-ready racks and infrastructure that are both functional and aesthetically pleasing

  • Leading telemetry and control system architecture for lab facilities, including sensor networks, DCIM (Data Center Infrastructure Management) platforms, BMS (Building Management Systems), and real-time environmental monitoring

  • Evaluating and scaling infrastructure to support constantly evolving power density and thermal load requirements driven by next-generation computing platforms

  • Collaborating with product and thermal engineering teams to translate system-level requirements into infrastructure designs that can be validated and iterated in the lab

  • Provide guidance to contractors and vendors throughout planning, procurement, and construction phases

  • Implement standardized commissioning processes for lab environments

What we need to see:

  • BS degree in Mechanical Engineering, or related field (or equivalent experience)

  • 8+ years of relevant MEP engineering experience, with at least 5 years focused on datacenter or critical facility infrastructure

  • Hands-on experience with cooling systems including direct liquid cooling (DLC/CDU), chilled water systems, and precision air cooling systems

  • Strong understanding of telemetry, control systems, and DCIM/BMS platforms used to monitor and manage critical infrastructure

  • Demonstrated experience working with A/E firms, general contractors, and equipment vendors

  • Knowledge of datacenter power systems including electrical distribution, UPS, generators, and power metering

  • Excellent communication skills with a proven record of teamwork across product engineering, facilities, and operations teams

Ways to stand out from the crowd:

  • Experience supporting lab or R&D environments where infrastructure must accommodate constantly evolving, high-density compute configurations

  • Familiarity with NVIDIA's product platforms or comparable accelerated computing hardware, and an understanding of their power and thermal demands

  • A portfolio of beautifully crafted server rack deployments as well as knowledge of relevant codes and standards including ASHRAE A2 thermal guidelines, NEC, BICSI, and TIA-942 datacenter standards

  • Experience with computational fluid dynamics (CFD) and flow network modelling tools to inform infrastructure planning decisions

  • PE (Professional Engineer) license or equivalent professional certification

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and collaborative people in the world working for us. Are you an infrastructure engineer who wants your work to power the future of AI? Come build the labs that build the future with us.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
152,000 USD – 253,000 USD for Level 4; and 184,000 USD – 287,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 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.

How we rate this

Senior MEP Engineer – Datacenter Lab Infrastructure at NVIDIA rates 26 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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