AI Systems Hardware Engineer - San Diego, California, United States of America
$174,000 - $261,000 USD yearly
Originally posted 5 June 2026 by the employer.
Map mixture-of-experts (MoE) and multimodal physical AI workloads across SoC, memory, and networking systems.
About the role
This role enables optimized mapping of AI workloads to Qualcomm's system-technology solutions by identifying system and technology bottlenecks for emerging AI models. Technical focus areas include mixture-of-experts (MoE), multi-tenant vector databases, and multimodal physical AI across the SoC, memory, and networking.
What you'll do
- Map emerging AI workloads using internal and external tools to AI accelerator systems. - Carry out what-if scenarios optimizing SoC, memory, networking, and technology features for power, performance, and TCO trade-offs. - Identify system and technology bottlenecks for workloads including mixture-of-experts (MoE), multi-tenant vector databases, and multimodal physical AI. - Determine which AI workloads are relevant across business units ranging from datacenters to physical AI and computing devices. - Collaborate across Architecture, product management, and software teams to define implementation strategies meeting system requirements.
What you'll need
- Bachelor's degree in Science, Engineering, or a related field with 6+ years of ASIC design, verification, validation, integration, or related experience (or Master's with 5+ years, or PhD with 4+ years). - Experience in ASIC design, verification, validation, or integration.
Nice to have
- Master's or Ph.D. in Electrical Engineering, Computer Science, or a related field. - Thorough understanding of E2E system KPI dependencies, such as power, performance, and TCO of emerging AI workloads (MoE, multi-tenant vector databases, multimodal physical AI). - High proficiency in scripting (Python or similar) to map newer workloads onto systems. - Advanced data analysis and interpretation skills.
Skills: ASIC design, system KPI, AI workloads, scripting, data analysis
This role has been open 200 days — well above the 52-day median for Hardware Systems Engineering roles.
Hardware Systems Engineering · AI ML Hardware
|
Open roles in category
1009
|
Median days open
52 d
|
Median salary
$155k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (1009 roles · 102 employers) |
|---|---|---|
| Open roles in this specialty | 36 | 1009 |
| Open roles in the wider Software, Firmware & Systems family | 735 | 6250 · 144 employers |
| Median days open | 55 d | 52 d (+3 d vs this employer) |
| Median salary (USD postings) | — | $155k |
Skills observed across this category: ASIC design, system KPI, AI workloads, scripting, data analysis
Who's hiring in this category
- Intel Corporation · 73 open roles · median 37 d
- KLA Corporation · 63 open roles · median 51 d
- Teradyne · 59 open roles · median 37 d
- NVIDIA · 51 open roles · median 69 d
- Applied Materials · 47 open roles · median 65 d
- AMD · 43 open roles · median 54 d
How we counted: 1009 open Hardware Systems Engineering (AI ML Hardware) roles from 102 employers tracked in the SemiconductorJobs index, counted 25 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.