Intern - NAND Product Engineering - Probe AI/ML - Fab 10N/X, Singapore
Originally posted 7 September 2026 by the employer — open 14 days.
Explore Agentic AI solutions for semiconductor yield analysis, test optimization, and data processing.
About the role
This internship focuses on applying Artificial Intelligence to semiconductor yield analysis, test optimization, data processing, and workflow automation within Product Engineering. The project involves developing Machine Learning models and exploring Agentic AI solutions for probe, wafer, test, and manufacturing data.
What you'll do
- Develop Machine Learning solutions for semiconductor yield, reliability, test-time, or cycle-time improvement.
- Explore Agentic AI applications that automate engineering analysis and documentation workflows.
- Transform high-volume semiconductor datasets into structured, analysis-ready information.
- Evaluate potential applications of Artificial Intelligence that improve engineering efficiency.
- Develop and evaluate predictive models for yield, product reliability, or test-time optimization.
- Prepare, clean, transform, and integrate engineering data for Machine Learning and Artificial Intelligence workflows.
What you'll need
- Basic programming knowledge in Python and familiarity with libraries such as Pandas, NumPy, or Scikit-learn.
- Understanding of Machine Learning concepts such as regression, decision trees, feature engineering, model validation, and performance evaluation.
- Interest in Artificial Intelligence agents, Large Language Models, workflow automation, or AI-Enabled engineering solutions.
- Strong analytical thinking and problem-solving ability.
- Clear written and verbal communication skills.
Nice to have
- Coursework or project experience in Machine Learning, data science, data engineering, Artificial Intelligence, or automation.
- Exposure to TensorFlow or PyTorch for image, text, or engineering log analysis.
- Awareness of Agentic AI frameworks or platforms such as LangChain or Microsoft Copilot Studio.
- Basic understanding of Machine Learning Operations, including model lifecycle, evaluation, deployment, and monitoring.
- Interest in cloud-based Artificial Intelligence technologies, including Microsoft Azure or Amazon Web Services.
Skills: machine learning, AI, yield analysis, test optimization, python
This role has been open 14 days — well below the 67-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
516
|
Median days open
67 d
|
Median salary
$232k
|
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 (516 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 32 | 516 |
| Open roles in the wider Software, Firmware & Systems family | 261 | 5829 · 143 employers |
| Median days open | 39 d | 67 d (−28 d vs this employer) |
| Median salary (USD postings) | — | $232k |
Skills observed across this category: machine learning, AI, yield analysis, test optimization, python
Who's hiring in this category
- Qualcomm · 106 open roles · median 99 d
- NVIDIA · 85 open roles · median 67 d
- AMD · 43 open roles · median 62 d
- Micron Technology (this employer) · 32 open roles · median 39 d
- Mobileye · 25 open roles · median 53 d
- Analog Devices · 14 open roles · median 24 d
How we counted: 516 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 21 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.