Remote ML Engineer Intern — Build AI for Asset Optimization

Siemens; Raleigh (NC); Hybrid; USD 40,000 - 47,000; Full time

Job summary

Siemens is hiring a Machine Learning Engineering Intern for a 10-week summer program. You will work with ML engineers to build, evaluate, and ship ML systems that enhance asset and operations insights. The role emphasizes rigorous, logic-based thinking and software development with Python.

The internship runs May 2027–August 2027, is remotely based in the United States, and requires onsite attendance in Raleigh, NC during the first week. After onboarding, the position is fully remote.

Qualifications

• Current enrollment in a master's degree program for the full duration of the internship.
• Working proficiency in Python.
• Comfort with foundational mathematics for ML including linear algebra, probability, and statistics.
• Ability to explain a complex argument clearly in writing and conversation.

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.

Skills

Python

Mathematics

Logical thinking

Writing

Education

Master's degree student

Tools

Git

SQL

Linux command line

Job description

Siemens is hiring a Machine Learning Engineering Intern for a 10-week summer program. You will work with ML engineers to build, evaluate, and ship ML systems that enhance asset and operations insights. The role emphasizes rigorous, logic-based thinking and software development with Python.

The internship runs May 2027–August 2027, is remotely based in the United States, and requires onsite attendance in Raleigh, NC during the first week. After onboarding, the position is fully remote.