Architecture Energy Modeling Engineering Intern - 2027 - Shanghai, China
Originally posted 15 September 2026 by the employer — open 3 days.
About the role
This internship focuses on researching, developing, and deploying methodologies to enhance the energy efficiency of NVIDIA's products. You will contribute to building energy models that integrate into architectural simulators, RTL simulation, and emulation platforms for NVIDIA GPUs and Tegra SOCs.
What you'll do
- Develop techniques to model, analyze, and reduce the power consumption of NVIDIA GPUs.
- Develop methodologies and workflows to select and run workloads to train models using machine learning and statistical techniques.
- Develop methodologies to improve the accuracy of energy models under constraints such as process, timing, floorplan, and layout.
- Correlate predicted energy from models created at different stages of the design cycle with silicon.
- Develop tools to debug energy inefficiencies observed in silicon, RTL, and architectural simulators.
- Prototype new architectural features, create energy models, and analyze system impact.
What you'll need
- Pursuing an MS degree.
- Strong coding skills in Python, C++.
- Background in machine learning, AI, and/or statistical modeling.
- Interest in computer architecture and energy-efficient GPU designs.
- Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
- Good verbal/written English and interpersonal skills.
Nice to have
- Familiarity with Verilog and ASIC design principles.
Skills: energy modeling, GPU, Tegra SOCs, machine learning, computer architecture
This role has been open 2 days — well below the 65-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
512
|
Median days open
65 d
|
Median salary
$226k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (512 roles · 77 employers) |
|---|---|---|
| Open roles in this specialty | 85 | 512 |
| Open roles in the wider Software, Firmware & Systems family | 955 | 5844 · 143 employers |
| Median days open | 64 d | 65 d (−1 d vs this employer) |
| Median salary (USD postings) | — | $226k |
Skills observed across this category: energy modeling, GPU, Tegra SOCs, machine learning, computer architecture
Who's hiring in this category
- Qualcomm · 105 open roles · median 99 d
- NVIDIA (this employer) · 85 open roles · median 64 d
- AMD · 42 open roles · median 65 d
- Micron Technology · 32 open roles · median 36 d
- Mobileye · 25 open roles · median 50 d
- Analog Devices · 14 open roles · median 21 d
How we counted: 512 open AI/ML Hardware Engineering (AI ML Hardware) roles from 77 employers tracked in the SemiconductorJobs index, counted 18 Sept 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.