Artificial Intelligence / Machine Learning Methods Intern (Summer 2027) (Onsite)

Pratt & Whitney•East Hartford, CT

21h•Onsite

About The Position

The AI/ML Methods group at Pratt & Whitney focuses on developing cutting-edge artificial intelligence and machine learning solutions to solve complex challenges in aerospace engineering, manufacturing, and operations. As an intern, you will have the opportunity to work alongside a team of experts and contribute to impactful projects shaping the future of aviation. As an Artificial Intelligence / Machine Learning Methods Intern at Pratt & Whitney, you will… Collaborate with team members to design, develop, and implement AI/ML models for applications such as predictive maintenance, anomaly detection, optimization problems, or natural language processing. Analyze large datasets from various sources to extract insights and validate model performance. Develop scripts or tools to automate data preprocessing, feature engineering, or model evaluation workflows. Document methodologies and results clearly for internal presentations or reports. This internship provides hands-on experience in applying AI/ML techniques within the aerospace industry while fostering professional growth through mentorship opportunities and exposure to real-world challenges. Engineering Interns at Pratt & Whitney work on challenging, meaningful, and impactful projects across our business. Our intern program seeks to help you develop an understanding of the aerospace industry and learn about our company and its operations.

Requirements

Must be pursuing Bachelor’s or Advanced degree in Computer Science, Data Science Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Mathematics or related Science, Technology, Engineering or Mathematics (STEM) major and actively enrolled through the completion of the internship session.
Must have a minimum of 60 hours of credit by the start of the internship session.
Minimum 3.0 Cumulative GPA
Experience may be obtained through on-the-job experience, research, coursework, or projects

Nice To Haves

Experience with cloud platforms (AWS/GCP/Azure) for ML workflows.
Experience with domain-specific areas such as physics-informed ML models or digital twins is a bonus but not required.
Experience programming with Python or other relevant languages; experience with libraries like TensorFlow, PyTorch, Scikit-learn is a plus.
Experience with machine learning algorithms (e.g., supervised/unsupervised learning) and statistical methods.
Experience working with data manipulation tools such as Pandas or NumPy; knowledge of SQL is advantageous.
Prior RTX internship, co-op, or work experience.

Responsibilities

Collaborate with team members to design, develop, and implement AI/ML models for applications such as predictive maintenance, anomaly detection, optimization problems, or natural language processing.
Analyze large datasets from various sources to extract insights and validate model performance.
Develop scripts or tools to automate data preprocessing, feature engineering, or model evaluation workflows.
Document methodologies and results clearly for internal presentations or reports.