AI Hardware Architecture
Originally posted April 3, 2026 by the employer. Relisted by the employer on November 14, 2026.
About the role
This role proposes, designs, and evaluates analog-computing hardware architectures to achieve energy-efficiency advantages in ML inference. The work spans theoretical modeling, simulation, hardware/software co-design, and experimental validation across AI, physics, and computer architecture.
What you'll do
- Propose, design, and evaluate analog-computing hardware architectures targeting high energy efficiency in ML inference.
- Drive invention, prototyping, and validation of core components for a novel computing platform.
- Work across theoretical modeling, simulation, algorithm development, and hardware/software co-design.
- Conduct experimental validation and technical roadmap planning in collaboration with a multi-disciplinary R&D team.
What you'll need
- Degree in a quantitative field (Physics, Electrical Engineering, Computer Science, or a related discipline), or equivalent research/project experience.
- Deep knowledge of and experience in at least one of: AI hardware architecture design or integrated-circuit design.
- Exposure to and familiarity with the basic principles and engineering practice of analog and/or other unconventional physics-based computing paradigms.
- Familiarity with the operation of modern (post-2017) generative AI models and their implications for analog computer systems design.
- Ability to communicate complex technical concepts across the full stack from algorithms to circuits.
Nice to have
- Deep understanding of the principles and engineering practice of analog or unconventional physics-based computing paradigms, with proven ability to design and evaluate these hardware architectures.
- Experience modeling and optimizing architectural energy consumption for AI workloads while maintaining ML performance.
- Experience with hardware-algorithm co-design where AI models and hardware are optimized simultaneously.
- Experience designing hardware specifically to run modern generative AI models.
- Experience with detailed systems design and evaluation using at least one type of emerging non-volatile memory (such as RRAM), and knowledge of tradeoffs across non-volatile memories.
Skills: AI hardware, hardware architecture, AI accelerator
More semiconductor jobs: AI chip design jobs · Mountain View jobs
First seen in our index 110 days ago, slightly above the 107-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
482
|
Median days since first seen
107 d
|
Category median salary (all employers)
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Unconventional AI | All employers we track in this specialty (482 roles · 72 employers) |
|---|---|---|
| Open roles in this specialty | 4 | 482 |
| Open roles in the wider Software, Firmware & Systems family | 6 | 6731 · 166 employers |
| Median days since first seen | 110 d | 107 d (−3 d vs this employer) |
| Median salary (USD postings) | n/a | $236k |
Skills observed across this category: AI hardware, hardware architecture, AI accelerator
Who's hiring in this category
- NVIDIA · 109 open roles · median 88 d
- Qualcomm · 104 open roles · median 123 d
- AMD · 21 open roles · median 128 d
- Micron Technology · 15 open roles · median 72 d
- Mobileye · 15 open roles · median 102 d
- Analog Devices · 14 open roles · median 51 d
How we counted: 482 open AI/ML Hardware Engineering (AI ML Hardware) roles from 72 employers tracked in the SemiconductorJobs index, counted 14 Nov 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there, and is counted in the wider Software, Firmware & Systems family row. Days are counted from when our index first saw each posting, not from the employer's original posting date.