Research Engineer/ Senior Research Engineer (FAB Data & Automation), IME

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A*STAR - Agency for Science, Technology and Research in Singapore is looking for a Data Analytics & AI Specialist to join their Data & Automation team. The ideal candidate will develop and deploy solutions using machine learning and statistical modeling to tackle complex challenges in fab operations. Required qualifications include a bachelor's degree in a relevant field and at least 2 years of relevant experience. Strong skills in Python and SQL are essential, as well as experience with cloud platforms like AWS or Azure. The position offers an opportunity to work on exciting projects in a dynamic environment.

Qualifications

• Minimum bachelor’s degree in Data Science, Computer Science or related field.
• 2+ years of experience in semiconductor manufacturing or fab automation.
• Strong programming skills in Python and SQL.
• Excellent teamwork and communication skills.

Responsibilities

• Develop and deploy data-driven solutions using machine learning.
• Design scalable data pipelines for high-volume fab data.
• Collaborate with teams to improve manufacturing outcomes.

Skills

Data analytics application

Machine learning techniques

Python programming

SQL

Statistical methods

Education

Bachelor’s degree in Data Science or related field

Tools

TensorFlow

PyTorch

AWS

Azure

GCP

Spark

Kafka

Job description

Job Description

We are seeking a creative and motivated Data Analytics & AI Specialist to join our Data & Automation team. In this role, you will develop and deploy data‑driven solutions using machine learning, statistical modeling, and AI techniques to solve complex challenges across fab operations—from wafer processing and defect detection to predictive maintenance and real‑time process control. You will collaborate closely with process engineers, equipment specialists and IT teams to transform raw fab data into actionable intelligence that enhances productivity, quality, and yield.

Key Responsibilities

• Design, develop, and implement scalable data pipelines to ingest, clean, and structure high‑volume, high‑velocity data from fab tools (e.g., sensors, MES, EDA, APC systems).
• Apply advanced analytics, machine learning, and AI techniques (e.g., computer vision, time‑series forecasting, anomaly detection, reinforcement learning) to improve manufacturing outcomes.

Build Predictive and Prescriptive Models for Applications Such As

• Yield prediction and root cause analysis.
• Equipment health monitoring and predictive maintenance.
• Real‑time process control and fault detection.
• Defect classification and pattern recognition.
• Collaborate with cross‑functional teams to translate business problems into analytical frameworks and measurable KPIs.
• Deploy and monitor ML models in production environments, ensuring reliability, scalability and compliance with fab data governance standards.
• Stay current with emerging AI/ML technologies and assess their applicability to semiconductor manufacturing challenges.
• Document methodologies, share insights through dashboards and reports, and support continuous improvement initiatives.

Required Qualifications

• Minimum bachelor’s degree in Data Science, Computer Science, Electrical Engineering, Industrial Engineering, Applied Mathematics or a related field.
• 2+ years of experience applying data analytics and/or machine learning in semiconductor manufacturing or fab automation.
• Knowledge of semiconductor processes (e.g., lithography, etch, deposition) or equipment data standards (SECS/GEM, GEM300).
• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL.
• Experience working with time‑series data, sensor data, or structured/unstructured manufacturing data.
• Familiarity with cloud platforms (AWS, Azure or GCP) and big data tools (e.g., Spark, Kafka).
• Understanding of statistical methods, experimental design and model validation techniques.
• Excellent problem‑solving, communication and teamwork skills.