Internship in Agentic AI (F/M/D), Alpnach

Help us grow and be more impactful! We are looking for a passionate intern in Agentic AI.

Internship Overview The internship duration is minimum 6 months, and enrollment in a Computer Science or Engineering program at ETH is mandatory.

The Predictive Analytics group is offering an internship focused on exploring how effectively LLM-powered agents can perform data analysis tasks using both real customer data and synthetic datasets.

Your Mission You will work closely with our PhD student, who is affiliated with the Computer Science Department at ETH Zurich. For highly motivated students, the internship may lead to a publication at a top-tier conference such as ICML, NeurIPS, ICLR, or AAAI.

Your Responsibilities

Contribute to the development of an AI agent designed to analyze and interpret industrial data for our clients.

Design and implement proof‑of‑concept solutions and demonstrators for various predictive analytics projects in collaboration with the team based in Alpnach.

Engage in academic research activities together with our PhD student, advancing knowledge and innovation in the field of LLM and Agentic AI.

Assist the team in various tasks.

Requirements

Ability to work on‑site in Alpnach, Switzerland, at least three times a week.

Strong proficiency in Python.

Enrollment in a Computer Science or Engineering program at ETH.

Familiarity with Git and Linux (Bash, SSH, etc.).

Theoretical knowledge of machine learning (e.g., completion of Introduction to Machine Learning or equivalent).

Preferred Qualifications

Demonstrated experience in building and deploying actively used applications.

Proven experience with agentic applications.

Research experience in machine learning or computer vision (e.g., publications).

Experience with customer‑facing tasks (presentations, slides, emails).

German language proficiency (C1).

Interpersonal Skills

Driven and motivated.

Good communication skills.

Highly collaborative.

Flexible and adaptable thinking / operating style.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity.

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