Machine Learning Engineering Intern - Summer 2027

Siemens is hiring a Machine Learning Engineering Intern to build, evaluate, deploy, and monitor machine learning systems that help customers improve asset and operations performance. The intern will work with ML engineers on data pipelines, model evaluation, production-quality code, and communicating project results.

Responsibilities:

• Build and maintain data pipelines that clean, label, and prepare datasets for model training
• Train, fine-tune, and evaluate machine learning models, and write clear reports on what worked and why
• Design evaluation methods and test cases that expose where a model's reasoning breaks down
• Write production-quality Python code, with tests and code review, that ships alongside our engineering team
• Help deploy and monitor models, tracking accuracy, drift, and failure cases after launch
• Present your work to the team in a final project showcase at the end of the internship

Requirements:

• We're hiring a Machine Learning Engineering Intern who is currently enrolled in a master's program and brings rigorous, logic-driven thinking
• This internship is built for people who think that way and have already started writing software
• Qualified Applicants must be legally authorized for employment in the United States and will not require employer sponsored work authorization now or in the future for employment in the United States
• Current enrollment in a master's degree program for the full duration of the internship
• At least one of the following: professional software engineering experience, including full-time, part-time, contract, or substantial open-source work; a bachelor's degree in Engineering, Philosophy, Theology, Mathematics, or another logic-focused discipline; or a recognized programming certification, such as a language certification or completed coding bootcamp
• Working proficiency in Python
• Comfort with foundational mathematics for machine learning, including linear algebra, probability, and basic statistics
• The ability to explain a complex argument clearly in writing and conversation
• Hands-on experience with a machine learning framework such as PyTorch, TensorFlow, or scikit-learn
• Familiarity with Git, SQL, and working in a Linux command line
• Coursework or projects in formal logic, ethics, decision theory, or statistics
• A portfolio, GitHub profile, or writing sample that demonstrates how you think through difficult problems
• A degree background outside Computer Science at the bachelor's or master's levels