At Endress+Hauser, progress happens by working together. As the global leader in measurement instrumentation, with over 17,000 employees shape the future in the field of process automation. Whether developing and realizing new technology as a team, collaborating to build instrumentation, or strengthening vital relationships with countless global industries, we work to create trusted relationships that help everyone thrive. As a family-owned company, we look beyond short-term moves and work to create a vision that is forward-thinking for our people, our clients, and the world at large.
We are looking for a Student Intern (ML Engineer) to join us and bring fresh ideas and energy to Endress+Hauser Digital Solutions. As part of our Reinach-based team, you will explore how data, machine learning, and artificial intelligence can shape the future of industrial automation. Endress+Hauser Digital Solutions is at the heart of our digital innovation, developing cutting-edge software and connectivity solutions that empower industries worldwide.
What is the role about?
Are you curious about how intelligent systems can solve real-world challenges? Do you enjoy working with data to discover new insights? Are you eager to experiment with the latest AI frameworks and put them into practice? If so, this role gives you the chance to apply your knowledge in a supportive environment where learning and innovation go hand in hand. You will work closely with experienced engineers, product teams, and data experts, contributing to the development of solutions that bring real value to customers in the process automation industry.
Which tasks will you perform?
You Will
* Collaborate with product and engineering teams to understand data requirements and contribute to AI-driven features
* Assist in designing and developing machine learning models for a wide variety of applications in the process automation industry
* Support data collection, preprocessing, and analysis for training and evaluating models
* Contribute to the development of scalable data pipelines and APIs for AI applications
* Participate in code reviews, agile development processes, and team discussions
* Explore and experiment with modern AI frameworks and libraries such as TensorFlow, PyTorch, or LangGraph
* Document your work and share insights with the team to foster learning and innovation
What do we expect from you?
You
* Are currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field
* Have a strong interest in applied machine learning, data engineering, and AI technologies such as LLMs and autonomous agents
* Bring basic programming skills in Python; familiarity with libraries like NumPy, pandas, or scikit-learn is a plus
* Understand fundamental ML concepts such as supervised learning, model evaluation, and feature engineering
* Have some exposure to cloud platforms (e.g., Azure, AWS, GCP) or version control tools (e.g., Git)
* Communicate well in English; German is a plus
* Are curious, proactive, and eager to learn in a collaborative environment
What can you expect from us?
* We are a family-owned, highly committed company with a sustainable vision
* We promote lifelong learning with versatile training and further education opportunities, internal knowledge transfer and e-learning
* Corporate pension plan and health management
How do you apply?
If this position sounds appealing to you, Simone Studer and Elina Lehmann will be pleased to hear from you. To apply we kindly ask you to upload your documents on our career page. Please send your CV and state your salary expectations and earliest possible start date. Please contact us at if you have any questions.
Applications sent to us by E-Mail can unfortunately not be considered due to Data Privacy Considerations.
Agencies, HR service providers, or similar entities are kindly requested to refrain from unsolicited submission of profiles and inquiries regarding potential collaboration. Currently, we do not engage with external service providers for this role. Any unsolicited applications will be disregarded and deleted without further consideration. We appreciate your understanding.