Machine Learning Engineering Intern - Summer 2027

Siemens

Raleigh (NC)

Hybrid

USD 40,000 - 47,000

Full time

5 hours ago
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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

At Siemens, we help organizations transform maintenance and operations through connected insights, AI-powered technology, and intelligent asset management solutions. Our software enables customers to manage the full lifecycle of assets, facilities, and infrastructure while improving efficiency, reducing risk, and optimizing long-term investments. By connecting data, people, and processes, we empower organizations to make smarter decisions, maximize asset performance, and achieve more resilient operations.

Description:

We're hiring a Machine Learning Engineering Intern who is currently enrolled in a master's program and brings rigorous, logic-driven thinking. You'll work alongside our ML engineers to build, evaluate, and ship machine learning systems that help customers get more from their assets and operations. We believe some of the best ML engineers reason like philosophers, engineers, and theologians: they define terms carefully, test assumptions, and follow an argument to its conclusion. This internship is built for people who think that way and have already started writing software. This 10-week Summer Internship will last between May 2027 and August 2027.

Location:

This position is remotely based within the United States. However, to facilitate onboarding and establish key relationships with the team, the successful candidate will be required to attend their first week of employment onsite in Raleigh, NC. Following onboarding, the role will be fully remote.

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.

You'll make an impact by:
  • 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.
This is howyou'llwin us over:
  • 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.
You'll Thrive Even More If You Also Bring:
  • 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.

At Siemens, you'll have the opportunity to grow your career while helping organizations operate smarter, safer, and more sustainably. We foster a culture of innovation, collaboration, and continuous learning, where employees are empowered to make a difference every day. If you're excited about solving real-world challenges and shaping the future of asset management, we encourage you to apply.

Our Commitment to Equity and Inclusion in our Diverse Global Workforce:

We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the every day with us.

Siemens maintains a Drug Free workplace in accordance with applicable law.

#AMSInternsFY27

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