3 months ago

GPU Power Architect - New College Grad 2026

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Contribute to energy-efficient GPU power modeling and architectural exploration for datacenter GPUs, developing power and performance models, and applying machine learning to optimize Perf/Watts for GenAI/HPC workloads in NVIDIA’s DGX and future datacenter products.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Entry level

Key Responsibilities

•Contribute to power estimation models and tools for GPU products and systems like NVIDIA DGX.
•Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.
•Help with Performance vs Power Analysis for NVIDIA future product lineup.
•Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms.
•Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.

Pay and Benefits

Salary: USD 100,000 - 166,750 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•Pursuing or recently completed a Bachelors or Masters in Electrical Engineering, Computer Engineering, or equivalent experience.
•Knowledge of energy efficient chip design fundamentals and related tradeoffs.
•Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS).
•Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques.
•Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch.

Education:

Skills:Problem-solvingAnalytical thinkingCollaboration

Tech Stack:PythonPandasNumPyPyTorchDVFS

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

3 months ago

GPU Power Architect - New College Grad 2026

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Entry level

Key Responsibilities

•Contribute to power estimation models and tools for GPU products and systems like NVIDIA DGX.
•Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.
•Help with Performance vs Power Analysis for NVIDIA future product lineup.
•Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms.
•Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.

Pay and Benefits

Salary: USD 100,000 - 166,750 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•Pursuing or recently completed a Bachelors or Masters in Electrical Engineering, Computer Engineering, or equivalent experience.
•Knowledge of energy efficient chip design fundamentals and related tradeoffs.
•Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS).
•Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques.
•Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch.

Education:

Skills:Problem-solvingAnalytical thinkingCollaboration

Tech Stack:PythonPandasNumPyPyTorchDVFS

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor