Hybrid AI & Workflow Optimization Intern

ASML; Eindhoven; Hybrid; EUR 8,900 - 13,000; Part time

Job summary

ASML's TWINSCAN Factory OE Quality department offers a business analytics/AI internship in the Netherlands to explore workflow optimization and AI applications. You will identify opportunities to improve recurring activities and support measurable operational improvements.

You will develop proof-of-concepts with Python, assess feasibility and impact, and present insights to stakeholders. The internship lasts at least 5 months, requires 3+ days per week, with 2 days on-site starting February 2027.

Qualifications

• Pursuing bachelor’s or master’s in CS/DS/AI.
• Experience with Python, data processing and generative AI.
• Ability to analyze processes and identify opportunities for improvement.
• Independent, analytical and proactive working style.
• Excellent English communication with stakeholders.

Responsibilities

• Analyze recurring activities, workflows and business processes.
• Identify inefficiencies, bottlenecks and opportunities for process improvement.
• Research and evaluate AI and automation solutions.
• Develop and validate proof-of-concepts using Python and data processing.
• Assess feasibility, impact and scalability of proposed improvements.
• Present recommendations and insights to stakeholders.

Skills

Python

Data processing

Generative AI

English communication

Independent working style

Proactive

Education

Bachelor’s or Master’s in CS/DS/AI

Tools

VS Code

Power BI

Power Automate

Power Query

Databricks

n8n

Lovable

Job description

ASML's TWINSCAN Factory OE Quality department offers a business analytics/AI internship in the Netherlands to explore workflow optimization and AI applications. You will identify opportunities to improve recurring activities and support measurable operational improvements.

You will develop proof-of-concepts with Python, assess feasibility and impact, and present insights to stakeholders. The internship lasts at least 5 months, requires 3+ days per week, with 2 days on-site starting February 2027.