Originally posted 17 September 2026 by the employer.
About the role
This role supports the exploration of AI memory and system environments, analyzing infrastructure trends, contributing to performance modeling, and supporting tool development to inform HBM architecture decisions.
What you'll do
- Research emerging trends in compute, networking, and storage infrastructure to understand future AI workloads.
- Support HBM architecture analysis by collecting and synthesizing data for bandwidth, latency, and system-level memory requirements.
- Help develop or refine simulation frameworks used to model AI cluster performance and memory subsystem behavior.
- Assist in building first-order performance models for HBM bandwidth, latency, GPU/CPU interactions, and memory hierarchy trade-offs.
- Participate in building trend dashboards using CSP benchmarks and industry datasets.
- Collaborate with mentors to explore architectural intercept opportunities for AI systems.
What you'll need
- Currently pursuing a Master’s degree or PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field.
- Strong foundational understanding of computer architecture, digital systems, and hardware/software interaction.
- Interest in memory subsystem design (HBM, DDR, caches) and its impact on AI/ML workloads.
- Deep understanding of LLM pipeline and critical bottlenecks.
- Programming experience in Python, C/C++, or similar languages.
Nice to have
- Exposure to AI workload behavior, ML model training pipelines, or large-scale system bottlenecks.
- Ability to turn research findings into concise technical summaries or recommendations.
- Comfort learning new tools, simulation frameworks, and data-analysis workflows.
Skills: AI workloads, HBM architecture, AI cluster performance, memory subsystem behavior, computer architecture
This role has been open 21 days — well below the 76-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
520
|
Median days open
76 d
|
Median salary
$235k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Micron Technology | All employers we track in this specialty (520 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 29 | 520 |
| Open roles in the wider Software, Firmware & Systems family | 262 | 6085 · 146 employers |
| Median days open | 63 d | 76 d (−13 d vs this employer) |
| Median salary (USD postings) | — | $235k |
Skills observed across this category: AI workloads, HBM architecture, AI cluster performance, memory subsystem behavior, computer architecture
Who's hiring in this category
- Qualcomm · 100 open roles · median 113 d
- NVIDIA · 92 open roles · median 57 d
- AMD · 40 open roles · median 69 d
- Micron Technology (this employer) · 31 open roles · median 63 d
- Mobileye · 19 open roles · median 71 d
- Analog Devices · 17 open roles · median 27 d
How we counted: 520 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 9 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.
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