Principal Datacenter HSIO Engineer

NVIDIA is hiring a Principal Datacenter HSIO Engineer in Santa Clara, United States. It pays $240k-$380k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Little AI ●○○○: aI is not part of the work.
Level classifies it as a lead role.
Level lists 2,600+ other open roles at NVIDIA.

AI in this role

NVIDIA is a learning machine that constantly evolves by seeking exciting opportunities that matter to the world, and that only we can solve. We attract the world’s best people, so we can achieve our highest aim: building a company that lets us do our life’s work, at the highest level of our craft. Join our new team building the next generation of datacenter infrastructure that powers the future of AI. We are seeking highly motivated technical experts to join our new organization leading datacenter product design.

What you'll be doing:

Drive end-to-end system architecture from silicon to rack level
Lead cross-domain optimization efforts involving power delivery, thermal design, signal integrity, and mechanical constraints
Develop innovative features at all levels (silicon/system) to help improve GPU performance
Collaborate with vendors and suppliers for interconnect (electrical/optical), power delivery, and memory solutions
Provide expertise and support to validation teams with planning and execution
Work with customers on an as-needed basis to help deliver products

What we need to see:

15+ years of experience in a rigorous technical hardware role interfacing with systems (HW system architecture, PCB design, mixed signal design, hardware validation, system verification, signal integrity, etc)
Master's degree (or equivalent experience) in Electrical Engineering or related field
Deeply inquisitive and able to use core technical competencies to provide direction on system architecture
Ability to see big picture tradeoffs for product success
Motivation and ability to manage concurrent projects and priorities with tight deadlines in a multifaceted environment
Excellent communication skills required to work well with multi-functional teams (software, firmware, marketing, mixed signal, etc.)
Previous experience with L10/L11
Deep understanding of system level (L11) power architecture tradeoffs
Knowledge and experience with modern optical communications (pluggables, CPO)
Strong signal/power integrity background with hands on lab experience (Oscilloscope, TDR, VNA)

Ways to Stand Out from the crowd:

Experience with applied ML frameworks, successful applications of AI/ML to hardware problems
Understanding of electrical vs mechanical tradeoffs
Proficiency with CAD simulation tools
Ability to think outside the box!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 240,000 USD – 379,500 USD.

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

Principal Datacenter HSIO Engineer at NVIDIA rates 7 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.