Unconventional AI
AI Hardware Architecture
Mountain View, CA +1 · Full-time · Posted Nov 26, 2025
- Location
- Mountain View, CA
Mountain View - Education
- MS/PhD or equivalent research/project experience is strongly preferred.
About the job
Propose, design, and evaluate analog-computing hardware architectures to improve the energy efficiency of machine-learning inference.
What you'll do
- Drive invention, prototyping, and validation of components of the computing platform.
- Model, simulate, develop algorithms, or conduct experimental validation as needed.
- Communicate technical concepts across teams spanning algorithms to circuits.
What they ask for
- Strong technical ability in a quantitative field such as Physics, Electrical Engineering, or Computer Science.
- Deep knowledge and experience in AI hardware architecture design or integrated-circuit design.
- Familiarity with analog or other unconventional physics-based computing principles and engineering practice.
- Familiarity with modern generative AI models and their implications for analog computer systems.
Nice to have
- Experience modeling and optimizing energy consumption for AI architectures while maintaining ML performance.
- Experience in hardware-algorithm co-design, generative-AI hardware, or emerging non-volatile memories such as RRAM.
Tools
RRAM
AI focus
Develop energy-efficient analog-computing hardware architectures for ML inference, including consideration of modern generative AI models.
Model-written summary · the original posting is authoritative