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AI Digitalization Co-op

Knorr-Bremse North America
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                                              Co-op, IT AI (Digitalization) 

 

Co-op opportunity for students majoring in Computer Science, Computer Engineering, IT, or Data Science. This role focuses on identifying opportunities to apply AI and leveraging AI tools to develop solutions for manufacturing and office environments. The ideal candidate is passionate about AI, possesses a strong technical foundation, and can drive awareness and understanding of AI within the organization. 

This job is for the FALL 2026 semester, August-December!

Job Responsibilities: 

 

AI Opportunity Identification & Implementation: 

Analyze current manufacturing and office processes to identify AI use cases that enhance efficiency, reduce errors, and optimize workflows. 

Develop and test AI models using Python and other AI tools to solve real-world problems in manufacturing and business operations. 

Collaborate with different departments to understand challenges and propose AI-driven solutions. 

Monitor industry trends and emerging AI technologies to recommend potential applications for the organization. 

 

AI Project Development: 

Work with IT teams to integrate AI solutions into existing systems and processes. 

Develop proof-of-concept AI models and applications for evaluation. 

Optimize AI algorithms for performance, accuracy, and efficiency. 

Document AI projects, methodologies, and outcomes for future reference and scalability. 

 

AI Advocacy & Training: 

Develop and facilitate AI training sessions for employees at different levels of technical expertise. 

Educate teams on the benefits, risks, and limitations of AI to ensure responsible and effective adoption. 

Assist in the development of AI-related policies, best practices, and ethical guidelines. 

 

Eligibility Requirements: 

Currently enrolled at an accredited college or university. 

Cumulative GPA of 3.0 or higher. 

Experience with programming languages, especially Python, and AI frameworks such as TensorFlow, PyTorch, or Scikit-learn. 

Familiarity with machine learning, natural language processing, or computer vision applications. 

Ability to communicate complex AI concepts to non-technical stakeholders. 

Prior experience with AI projects (coursework, personal projects, or internships) is a plus.