Senior Architecture Energy Modeling Engineer - CA, Santa Clara, United States
$136,000 - $264,500 USD yearly
Originally posted 21 August 2026 by the employer.
About the role
This role involves researching, developing, and deploying methodologies for energy modeling to improve the energy efficiency of NVIDIA GPUs, CPUs, and Tegra SOCs. The position focuses on building energy models that integrate into architectural simulators, RTL simulation, emulation, and silicon platforms.
What you'll do
- Develop an energy-efficient GPU in collaboration with architects, designers, and performance engineers.
- Identify key design features and workloads for building Machine Learning based unit power/energy models.
- Develop and own methodologies and workflows to train models using ML and/or statistical techniques.
- Improve the accuracy of trained models by using different model representations, objective functions, and learning algorithms.
- Develop methodologies to estimate data movement power/energy accurately.
- Correlate predicted energy from models built at different design cycle stages, bridging early estimates to silicon.
What you'll need
- MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
- 5+ years experience.
- Strong coding skills in Python, C++.
- Background in machine learning, AI, and/or statistical modeling.
- Background in computer architecture and interest in energy-efficient GPU designs.
- Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
- Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.
Nice to have
- Familiarity with Verilog and ASIC design principles.
Skills: Machine Learning based power models, energy modeling, GPU, AI accelerators, computer architecture
This role has been open 45 days — well below the 76-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
504
|
Median days open
76 d
|
Median salary
$230k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (504 roles · 75 employers) |
|---|---|---|
| Open roles in this specialty | 85 | 504 |
| Open roles in the wider Software, Firmware & Systems family | 971 | 5996 · 146 employers |
| Median days open | 71 d | 76 d (−5 d vs this employer) |
| Median salary (USD postings) | — | $230k |
Skills observed across this category: Machine Learning based power models, energy modeling, GPU, AI accelerators, computer architecture
Who's hiring in this category
- Qualcomm · 99 open roles · median 109 d
- NVIDIA (this employer) · 84 open roles · median 72 d
- AMD · 42 open roles · median 66 d
- Micron Technology · 30 open roles · median 58 d
- Mobileye · 18 open roles · median 73 d
- NXP Semiconductors · 15 open roles · median 63 d
How we counted: 504 open AI/ML Hardware Engineering (AI ML Hardware) roles from 75 employers tracked in the SemiconductorJobs index, counted 6 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.