Internship - AI/ML implementation on Chip Verification flow
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Tools in this posting
- Python
- SQL
- MySQL
- Django
Source — Tool mentions in context
Internship Learning Outcomes: * EDA Tools Application: Demonstrate knowledge gained from coursework EDA tools after gathering raw data and undertaking data structuring. * Automation & Data Processing: Apply data analysis and processing by automation using python and/or perl scripts, interfacing to databases such as MySQL and UNIX servers. * Practical Engineering Exposure: Obtain hands-on experience applying engineering knowledge towards enhancing team efficiency and effectiveness through Machine Learning. Your Profile
Qualifications and skills to help you succeed * Education: Bachelor/Masters’ Degree in Engineering / Computer Science / Information Technology / Business Analytics / Data Science. * Programming & Scripting: Strong skills and interest in scripting and programming (python and/or perl). * Database & SQL: Knowledge and skills in database such as SQL/Django will be added advantage. * Related Tools & Concepts: Knowledge in Artificial Intelligence / Data Mining / Machine Learning / UNIX / JIRA will be a plus. * Preferred Intake: Jan 27 – May/June 27. Contact: Hillary Woo
Job description
Improve the current Chip Verification flow with AI/ML implementation to increase efficiency.
Your Role
Key responsibilities in your new role
* Verification Flow Optimization: Develop new or enhance existing flows to improve efficiency based on Machine Learning implementation using automation.
* AI/ML Decision Support: Use data mining and machine learning to make automated decisions.
* Cross-Functional Collaboration: Co-work with multiple interfaces to understand verification flow requirements to implement the automation.
Internship Learning Outcomes:
* EDA Tools Application: Demonstrate knowledge gained from coursework EDA tools after gathering raw data and undertaking data structuring.
* Automation & Data Processing: Apply data analysis and processing by automation using python and/or perl scripts, interfacing to databases such as MySQL and UNIX servers.
* Practical Engineering Exposure: Obtain hands-on experience applying engineering knowledge towards enhancing team efficiency and effectiveness through Machine Learning.
Your Profile
Qualifications and skills to help you succeed
* Education: Bachelor/Masters’ Degree in Engineering / Computer Science / Information Technology / Business Analytics / Data Science.
* Programming & Scripting: Strong skills and interest in scripting and programming (python and/or perl).
* Database & SQL: Knowledge and skills in database such as SQL/Django will be added advantage.
* Related Tools & Concepts: Knowledge in Artificial Intelligence / Data Mining / Machine Learning / UNIX / JIRA will be a plus.
* Preferred Intake: Jan 27 – May/June 27.
Contact:
Hillary Woo
#WeAreIn for driving decarbonization and digitalization.
As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.
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This means 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. We base our recruiting decisions on the applicant´s experience and skills. Learn more about our various contact channels.
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Click here for more information about Diversity & Inclusion at Infineon.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.infineon.com. The employer’s form will show what is required.
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Source & posting history
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- Status in our records
- Active
- First seen by us
- Aug 14, 2026
- Recorded sightings
- 84
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Jul 20, 2026
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