📍
Tel Aviv, Israel

Physical Design Power Optimization Engineer

2 years experience
Technology & Digital
Engineering
Posted:
January 6, 2026

Nvidia

GPUs and accelerated computing company
76.6
Palpable Score
Apply >view company >

NVIDIA is looking for best-in-class Physical Design Power Engineer to join our outstanding Networking Silicon Power engineering team, developing the industry's best high-speed communication devices, delivering the highest throughput, lowest latency and best Power! Come and take a part in designing our groundbreaking and innovating chips, enjoy working in a meaningful, growing and highly professional environment where you make a significant impact in a technology-focused company.

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What you will be doing:

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What we need to see:

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About the company

Nvidia

Company overview
NVIDIA designs GPUs and full-stack accelerated computing platforms used in gaming, professional visualisation, AI, and data centres. NVIDIA also builds networking and systems products for large-scale computing, plus software platforms such as CUDA and AI libraries that developers use to train and run models. NVIDIA sells to cloud providers, enterprises, researchers, and OEM partners, alongside a large consumer gaming ecosystem. NVIDIA is headquartered in Santa Clara, California and operates globally.

Locations and presence

NVIDIA’s corporate headquarters is in Santa Clara, California, and NVIDIA operates across dozens of countries (38 countries reported for fiscal year 2025). NVIDIA reports a “flexible work environment” with work-from-home under certain conditions, with day-to-day expectations varying by team and role.

Palpable Score

76.6
/ 100
NVIDIA is a strong early-career option because NVIDIA runs a clear set of student and new-grad pathways, and NVIDIA positions internships as the main pipeline into early-career hiring. The main friction point is hiring consistency: NVIDIA publishes an applicant-facing process, but public interview reports still include ghosting and uneven closure. Pay and intern experience signals are strong, while long-run early-career outcomes are not published as metrics candidates can easily compare.
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