Rtl Power Optimization – New College Grad 2026

NVIDIA

Base: 116,000 usd - 189,750 usd (level 2); 136,000...
Not specified
Rtl power optimization fundamentals
Python programming skills
Machine learning and artificial intelligence
NVIDIA is seeking a new college graduate for the Rtl Power Optimization role, focusing on AI-driven power optimization for GPU and networking chips. The position emphasizes collaboration with various engineering teams to enhance power efficiency and requires technical expertise in electrical engineering, digital design, and machine learning

Job Summary

  • Our team is privileged to work on Power Optimization of Data center, gaming and automotive GPU chips.
  • You will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to study and implement power analysis and reduction techniques for NVIDIA's next generation GPUs and Networking products.
  • Your contributions will help us gain early insight into energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements.

Matching Summary

Match Score: 85

NVIDIA is seeking a new college graduate for the Rtl Power Optimization role, focusing on AI-driven power optimization for GPU and networking chips. The position emphasizes collaboration with various engineering teams to enhance power efficiency and requires technical expertise in electrical engineering, digital design, and machine learning.

Salary

Base: 116,000 USD - 189,750 USD (Level 2); 136,000 USD - 218,500 USD (Level 3); Bonus/Equity: equity; Benefits: benefits

Skills & Requirements

Must-have

  • RTL power optimization fundamentals
  • Python programming skills
  • Machine Learning and Artificial Intelligence
  • pre-silicon power analysis tools
  • low-power design patterns at RTL

Nice-to-have

  • diverse, encouraging environment
  • creative and autonomous
  • forward-thinking and hardworking people

Key Requirements

  • MS or PhD in Electrical Engineering, Computer Engineering, or related fields
  • coursework or experience in AI, Digital Design and VLSI concepts
  • Knowledge of backend flows
  • Familiarity with RTL implementation of low-power techniques
  • Exposure to industry power analysis tools
  • Previous experience debugging RTL or gate-level power anomalies

Work Rights

Not specified

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