N

NVIDIA

Designs the chips and software that power AI

Principal Power and Thermal Architect

Full-TimeDeadline 9/27/26
$232k - $368k/yr+ Equity
Expert
Bachelor's, Master's, PhD
Santa Clara, CA, USA
In Person
Mechanical EngineeringThermal & Fluids Engineering
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • A BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • At least 15 years of experience in system-level power, thermal, or related architecture, with deep expertise in at least one of system power management, system thermal architecture, platform energy architecture, workload-aware power and thermal controls, or memory co-design.
  • External technical recognition, premier publications, patents, or industry standards contributions, together with active contributions to standards bodies, consortia, or external technical communities.
  • A track record of taking research-grade ideas through system co-design and into measurable product impact.
  • Demonstrated multifunctional influence aligning teams across the company without direct reporting authority.
Responsibilities
  • Architect next-generation system-, platform-, and datacenter-level power and thermal co-design solutions and scan internal research, academia, standards bodies, and silicon, memory, packaging, and platform partners for emerging developments.
  • Build the product-differentiation case for candidate ideas by evaluating performance, power, reliability, schedule, and cost, and determine which ideas are worth pursuing.
  • Lead end-to-end co-design from concept to product and drive alignment across architecture, VLSI, software, platform, packaging, and operations teams to bring selected technologies into production.
  • Shape innovation across workload-aware power and thermal controls, closed-loop platform telemetry, datacenter-class power compliance, platform-scale energy buffering, advanced cooling intercepts, and emerging memory co-design.
  • Maintain a living intercept pipeline, track candidates, productization status, decision gates, and product axes, and brief SCG and broader NVIDIA leadership on future priorities.
  • Collaborate with system architects, platform and software engineers, manufacturing partners, and external researchers to bring next-generation products to market.
Desired Qualifications
  • A PhD or equivalent experience with sustained research contributions after entering industry.
  • Machine learning or data-driven techniques applied to system power, thermal modeling, or design-space exploration.
  • Background in system reliability and variability, managing aging based on usage patterns, reliability, availability, and serviceability, lifecycle management, and the intersection with power and thermal.
  • Hands-on familiarity with emerging memory technologies, including advanced high-bandwidth memory and stacked memory.
  • Active contributions to standards bodies, consortia, or external technical communities.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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Yahoo Finance
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Yahoo Finance
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Nvidia unveils cuPotential as chip leaders adopt CUDA-X for AI-defined fabs, with up to 30x speedups

NVIDIA announced on October 14, 2026 that semiconductor leaders are adopting its CUDA-X libraries to build AI-defined fabs, factories where AI helps engineers optimise processes and fix production issues. The news came at SEMICON West in San Francisco. The company introduced cuPotential, a library for building AI agents that simulate how atoms and molecules interact. In early-access testing, it sped up already GPU-optimised workflows by an additional 2-3x. Synopsys is among the early users. Lam Research expects NanoVDB, an open source 3D data library, to speed up some wafer-etch modelling by up to 30x. Applied Materials, Cadence, KLA, and Siemens are also using NVIDIA's tools across chip design, manufacturing, and testing.