AI/ML Engineering Co-op

Parker Hannifin • Elyria, OH

23h • Onsite

About The Position

In Motion Systems Group and Hydraulic Valve Systems Division, we play a pivotal role in applications that change our world. We are in almost everything that moves. With our wide range of technologies, we help our customers solve their most complex engineering challenges by living our purpose: enabling engineering breakthroughs that lead to a better tomorrow. We believe that our team members are our key assets and that a diverse workforce is a driving force to bring our purpose to life. We foster a culture where every team member feels safe, included and empowered. We all belong, we all matter, and we all make a difference. We have an exciting opening for a AI/ML Engineering Co-op in Elyria, Ohio. This is an on-site opportunity starting in the fall.

Requirements

• Master’s student in AI/ML (or related field) with a bachelor’s in mechanical engineering.
• Local candidate available to be on site for a minimum of 2 semesters.
• Coursework or hands-on exposure in: Machine Learning / Deep Learning, Data Structures & Algorithms, CAD/CAM, Manufacturing Processes / Machining, and Numerical Methods.
• Simulation experience (FEA and/or CFD) - Ansys Mechanical and Fluent preferred.
• Practical experience with Python and ML frameworks (PyTorch or TensorFlow).
• Familiarity with basic software engineering tools: Git, Docker, and cloud fundamentals (AWS/GCP/Azure).
• Familiarity with CNC concepts (G-code, toolpaths, feeds & speeds) and CAD tools.
• Coursework or project experience in Generative AI / LLMs, code generation, or transformer models.
• Experience with physics-constrained learning (PINNs).
• Exposure to MLOps, model deployment, and automated testing.
• OCR/document understanding
• Unity / VR app development or 3D visualization experience.

Responsibilities

• Prototype AI/ML solutions for manufacturing automation and product development.
• Develop generative-AI workflows to produce and validate CNC (G-code) from CAD/CAM inputs.
• Integrate physics-informed techniques (e.g., PINNs) into models for improved reliability.
• Build OCR/document-ingestion pipelines and connect to downstream ML systems.
• Support Unity/VR visualizations as needed and deliver demos, reports, and handoff-ready code.

What This Job Offers

• Career Level: Mid Level