Full-Time

Senior Power Integrity Engineer

LPU Packaging

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$196k - $310.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

In Person

Master's, PhD

Category
Electrical Engineering (1)
Required Skills
Oscilloscope

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Requirements
  • MS or PhD in Electrical Engineering or a related field, or equivalent experience
  • 12+ years of relevant work experience in Power Integrity
  • A strong background in power integrity for high-current, low-voltage rails within large GPUs, ASICs, or CPUs
  • Proven ownership of the chip-package-board PDN design and sign-off process
  • Hands-on experience with FCBGA, 25D/3D integration, HBM, or similar high-power, high-pin-count packages
  • Direct experience in the co-design of bump/ball maps, power/ground planes, and decoupling capacitor networks
  • Proficiency with frequency-domain PDN impedance analysis and time-domain transient/droop simulation tools (eg, PowerSI, PowerDC, Sigrity, RedHawk, Totem, HFSS, SIwave, ADS, or SPICE)
  • A deep understanding of board-level PDN design, including stack-up definition, plane partitioning, and VRM placement on high-layer-count accelerator boards
  • Experience in executing lab measurements using VNAs, oscilloscopes, and PDN analyzers to correlate measured noise and droop to original specifications
Responsibilities
  • Define best‑in‑class power delivery design and optimization practices from die/package through board, tray, and rack levels for the full product development cycle
  • Own the PI specification and methodology for assigned products, defining PDN targets including impedance, droop, noise, and transient response for GPU, HBM, and high‑speed SerDes
  • Architect package‑level PDNs by collaborating with design teams on bump/ball maps, via structures, and decoupling strategies for FCBGA and 25D/3D integrations
  • Drive system‑level PI design, including board‑level PDN planning, decap placement, and VRM interfaces while co-optimizing with SI, thermal, and mechanical teams
  • Perform PI extraction and simulation for advanced packages and develop integrated chip–package–board co‑simulation flows using industry-standard tools
  • Generate and deploy reusable PI models, such as SPICE, S-parameter, and IBIS-AMI, for use by internal and external partners
  • Define and execute comprehensive lab validation plans to correlate measured impedance, noise, and droop against simulation data and specifications
  • Debug complex system‑level issues including rail noise, jitter‑induced errors, resets, and margin loss during hardware testing and validation
Desired Qualifications
  • Demonstrated leadership of end-to-end PI for a major GPU, CPU, or ASIC program from initial concept through mass production
  • Experience with data center or cloud hardware, specifically regarding rack-level power distribution and how PI choices impact performance headroom
  • Background in co-designing SI and PI for high-speed interfaces like PCIe, NVLink, CXL, or Ethernet SerDes to mitigate jitter and noise coupling
  • Strong communication skills with the ability to clearly explain complex PDN trade-offs and risks to both technical teams and program stakeholders

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA reported $215.9 billion fiscal 2026 revenue, up 65%, on February 25, 2026.
  • The August 10, 2026 Wall Street financing pact opens more buyers for NVIDIA hardware.
  • Nemotron 3.5 Lightning boosts ecosystem lock-in while driving cheap GPU demand.

What critics are saying

  • US Commerce tightened China chip controls again on May 31, 2026.
  • The $500 billion financing push ties growth to GPU resale values and customer defaults.
  • An AI hardware glut from AMD, Huawei, or Chinese foundries crushes collateral and pricing.

What makes NVIDIA unique

  • CUDA remains the default software moat for AI training and deployment.
  • NVIDIA secured SK Hynix as its largest memory partner in June 2026.
  • Vera Rubin and Blackwell keep NVIDIA ahead in rack-scale AI systems.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-3%
CNBC
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Cointime
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Yahoo Finance
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CNBC
Aug 11th, 2026
Nvidia releases first open-source AI model after CEO Huang's open letter debut

Nvidia has released Nemotron 3.5 Lightning, its first open-source AI model since CEO Jensen Huang entered the open-source AI debate. The model was developed particularly for autonomous AI agents and will be available on HuggingFace and Nvidia's website. Huang previously argued that open-weight models allow companies greater control, spur competition, and bring down pricing. For Nvidia, open-source AI boosts chip sales, as the models still require GPUs to run. Companies including CodeRabbit and Harvey have tested the model. Nvidia also released NeMo Switchyard software to determine the most appropriate and cost-effective AI model for specific tasks. Nvidia used distillation techniques to give Nemotron 3.5 Lightning capabilities similar to its larger models.