Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 5
Machine Learning @ 3
Data Analysis @ 5
System Architecture @ 3
PyTorch @ 5
Pandas @ 5
GPU @ 3
AI @ 3
GenAI @ 3
HPC @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is a world leader in energy-efficient high-performance products. Join NVIDIA's Applied Power Architecture team to develop state-of-the-art GPUs that power AI, HPC, Automotive, GeForce, and Mobile products. This role focuses on improving Perf/Watt for GPUs and datacenter systems.
Responsibilities
- Contribute to power estimation models and tools for GPU products and systems (e.g., NVIDIA DGX/HGX based datacenters).
- Early GPU and system architecture exploration with focus on energy efficiency and TCO improvements at the GPU and datacenter level.
- Perform performance vs. power analysis and track ASIC milestones for future product lineups.
- Deploy machine learning techniques to develop accurate power and performance models of GPUs, CPUs, switches, and platforms.
- Understand workload characteristics for GenAI/HPC workloads at datacenter scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.
- Model and analyze technologies such as high-speed and high-density interconnects.
Requirements
- MSEE/MSCE or equivalent experience, with 2+ years of experience related to power/performance estimation and optimization techniques.
- 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-software architectures, and performance/power modeling techniques.
- Proficiency with Python and data analysis packages such as Pandas, NumPy, and PyTorch.
- Familiarity with performance monitors/simulators used in modern processor architectures.
Compensation
- Base salary range (Level 2): 116,000 USD - 189,750 USD per year.
- Base salary range (Level 3): 136,000 USD - 218,500 USD per year.
- You will also be eligible for equity and benefits (see company benefits link). Applications accepted at least until January 13, 2026.