Internship: Innovation Engineering (non-thesis)

Internship opportunity in Innovation Engineering

Job Description

Start Date: September 2026

Duration: 6-12 months

Type: Internship (non-thesis)

Please note: you need to be officially enrolled at the university for the whole internship duration.

We are looking for a motivated intern with a background in electronic engineering, software engineering, computer engineering, or a related technical discipline. The ideal candidate has a strong interest in software development.

We are an AI-first team. AI tools — including LLMs for code generation, analysis, and problem-solving — are central to how we work. You'll be expected to use AI as a daily driver in your development workflow, not just as a topic of study.

In this internship, you will contribute to the further development, improvement, and modernization of existing Python-based software used for test equipment and automated test workflows. The assignment will focus on improving the structure, usability, maintainability, and intelligence of the software platform. Typical activities may include extending existing codebases, refactoring and debugging Python code, improving interfaces to measurement or test systems, supporting data processing and visualization, and creating clearer reporting or user workflows.

An important part of the assignment will be to bring an innovative contribution to the test automation environment. This could include, for example, exploring how AI or advanced data analysis can be used to detect anomalies in test results, improve test efficiency, support predictive diagnostics, or make the software easier to use and maintain. At the end of the internship, the expected outcome is a working prototype or implemented software improvement that demonstrates clear added value, together with documentation, validation results, and recommendations for further development.

The candidate should be fluent in Python and comfortable working with existing code. Experience with software development practices such as version control, documentation, testing, and structured debugging is beneficial. Experience with LabVIEW is considered a plus. A strong interest in AI, automation, and engineering problem-solving is highly valued. We are looking for someone who is curious, analytical, structured in their approach, and eager to deliver a meaningful technical contribution to intelligent and reliable test automation.

Your role:

• Improve and extend the existing Python-based test automation platform to improve structure, usability, and maintainability.
• Explore and prototype AI-based solutions such as anomaly detection in test results, predictive diagnostics, and intelligent reporting that add clear value to the test workflow.
• Improve interfaces between the software platform and measurement or test equipment, ensuring reliable and efficient automated test execution.
• Create clearer data visualization, reporting, and user-facing workflows that make the platform easier to use and interpret.
• Write clean, well-structured, testable Python code — leveraging AI-assisted code generation as a core part of your workflow, while maintaining engineering rigour and understanding of what the code does.
• Continuously explore emerging AI and automation technologies and recommend enhancements to the test automation environment.

You're the right fit if:

• Currently pursuing a Bachelor's or Master's degree in Electronic Engineering, Computer Engineering, Embedded Systems, or a related technical discipline.
• Strong programming skills in Python, with a focus on writing clean, maintainable, and well-structured code.
• Comfortable using AI tools such as LLM-based code assistants and copilots as part of your development workflow — and able to critically evaluate and refine AI-generated output.
• Comfortable working with existing codebases — reading, refactoring, debugging, and extending software written by others.
• Interest or experience in software that interacts with hardware: test equipment, measurement systems, instrument control, or embedded interfaces.
• Familiarity with software development practices such as version control (Git), testing, documentation, and structured debugging.
• A strong interest in AI, automation, and how intelligent software can improve engineering workflows.
• Any exposure to LabVIEW or instrument communication such as VISA or SCPI is a nice to have, but not required.
• You're a self-starter who is curious, analytical, structured in approach, and eager to deliver a meaningful technical contribution.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

Philips is a health technology company.