Senior Staff / Principal Engineer - Advanced Analytics & Artificial Intelligence (Test Engineering)

Infineon Technologies AG; Singapore; On-site; SGD 70,000 - 95,000; Full time

Job summary

Infineon Technologies AG in Singapore is seeking an AI Engineer to lead the development of intelligent test programs. This role entails using AI to transform complex data into actionable insights, optimizing test processes, and collaborating with cross-functional teams for product excellence.

The ideal candidate will have a Bachelor’s or Master’s degree in a relevant field and 5-10 years of experience in semiconductor test engineering, with proficiency in programming and strong analytical capabilities.

Qualifications

• 5–10 years of experience in semiconductor test or product engineering.
• Strong knowledge of IC development lifecycle, wafer test, yield optimization.
• Hands-on experience with machine learning and large-scale data analytics workflows.

Responsibilities

• Lead development and continuous improvement of test programs.
• Leverage AI to analyze large-scale test datasets.
• Collaborate with cross-functional teams for new product introduction.

Skills

Programming (Python, C++, Java)

Statistical Methods (DOE, SPC)

Analytical Capabilities

Machine Learning / AI

Education

Bachelor’s or Master’s Degree in Electrical & Electronic Engineering

Tools

ATE platforms

Job description

Overview

From data to deployment, join us in building intelligent systems. As an AI Engineer, get ready to program the intelligence behind the chips, transform complex data into actionable insights, and create cutting‑edge solutions that redefine industries and solve tomorrow's challenges.

Your Role

In Your New Role You Will:

Test Engineering Leadership

• Lead the development, release, and continuous improvement of test programs and test packages across product lifecycles.
• Drive engineering support for qualification, sampling, and high‑volume production, including grading strategies.
• Perform failure analysis, debug, and yield optimisation in collaboration with design, hardware, and product teams.
• Deliver test time reduction, yield improvement, and test quality enhancement initiatives.
• Ensure clear and actionable reporting of test results, root cause analysis, and engineering insights.

AI-Augmented Test Engineering

• Leverage AI and machine learning (ML) to analyse large‑scale test datasets for:
  • Yield trend identification
  • Outlier and anomaly detection
  • Predictive failure analysis
• Apply domain‑specific AI systems to enable data‑driven test decision‑making and optimisation.
• Develop intelligent test strategies using analytics to:
  • Reduce test cost and complexity
  • Improve coverage and product quality
• Work with cross‑functional teams to implement automated data pipelines and AI‑enabled test analytics platforms.
• Champion the adoption of augmented engineering, combining engineering judgment with AI insights.

Collaboration & Impact

• Collaborate with design, product, and process engineering teams to ensure strong correlation between test and product performance.
• Support new product introduction (NPI) and ramp‑to‑production phases.
• Interface with test equipment suppliers and pattern vendors to enhance test solutions.
• Mentor and guide engineers, contributing to capability building in AI‑enabled test engineering.

Your Profile

Qualifications and skills to help you succeed

Degree Requirements

• A Bachelor’s or Master’s Degree in Electrical & Electronic Engineering, Microelectronics, or a related field.
• 5–10 years of experience in semiconductor test or product engineering.

Strong knowledge of

• IC development lifecycle (design, validation, production, reliability)
• Wafer test, final test, and yield optimisation
• ATE platforms and test hardware

Technical Skills

• Proficiency in programming (Python, C++, Java) for test and data analysis.
• Experience with statistical methods such as DOE, SPC, and correlation analysis.
• Strong analytical capabilities in test data interpretation and debugging.
• AI & Data Capabilities (Key Requirement)

Hands‑on Experience or Strong Exposure to

• Machine learning / AI applied to engineering or test data.
• Large‑scale data analytics workflows.
• Familiarity with:
  • Domain‑specific AI systems for semiconductor test/yield analytics.
  • Predictive modeling and anomaly detection techniques.
  • Ability to translate engineering challenges into data‑driven, AI‑enabled solutions.

Experience We Value

• Experience in automotive SoCs, microcontrollers, or high‑reliability products.
• Proven track record in:
  • Yield improvement and test optimisation
  • NPI and production ramp activities
• Exposure to AI‑based automation or smart manufacturing systems is a strong advantage.

Contact

Sherlene Ong

Equal Opportunity Statement

We embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect, and tolerance and are committed to give all applicants and employees equal opportunities.