Artificial Intelligence and Machine Learning Intern - Summer 2027

Scope of Position

As part of an engineering and digital transformation team, use fundamental understanding of data analytics, artificial intelligence, machine learning, and manufacturing processes to complete key summer project deliverables in optical fiber and cable manufacturing. This role is designed for a current college student who is actively pursuing a degree and looking to apply classroom learning to real manufacturing problems.

• Use scientific method and data-driven problem solving to design analyses, experiments, and prototypes that support product, process, equipment, quality, or cost improvements.
• Analyze manufacturing, process, sensor, quality, and/or machine vision data to identify patterns, drivers, and opportunities for improvement.
• Develop and test AI/ML, statistical, automation, or visualization solutions under the guidance of experienced engineers and digital professionals.
• Provide recommendations, present findings, and document project work in a way that can be understood by engineering, operations, and leadership stakeholders.

Program Benefits

• Competitive salaries
• Housing assistance
• Travel reimbursement

Intern Activities

• Social and networking events
• Volunteer opportunities
• Community Involvement

Responsibilities

• While participating in a team environment, own one or more defined summer project objectives that support Corning’s manufacturing and digital transformation priorities.
• Interface with engineering, operations, quality, controls, IT/digital, and other support groups to understand process context, data sources, constraints, and potential implementation impact.
• Clean, structure, and analyze datasets using appropriate statistical, visualization, and AI/ML techniques.
• Build proof-of-concept models, scripts, dashboards, algorithms, or analytical tools using tools such as Python, SQL, Power BI, MATLAB, C/C++, C#, or similar platforms.
• Support projects involving machine vision, sensor technology, process control, automation, predictive analytics, anomaly detection, process capability, or model-based decision support.
• Review performance data from analyses, experiments, or prototypes and effectively draw conclusions based on evidence.
• Document assumptions, data sources, analysis methods, model performance, limitations, and recommended next steps.
• Communicate effectively with personnel at various levels, including project teams, manufacturing stakeholders, and engineering leaders.

Requirements

• Currently pursuing a BS or MS degree in Data Science, Computer Science, Computer Engineering, Electrical Engineering, Industrial Engineering, Applied Mathematics, Statistics, Mechanical Engineering, Chemical Engineering, or a related technical field.
• Must be actively enrolled in an accredited college or university during the internship and have at least one academic term remaining after the internship concludes.
• Rising junior, senior, or graduate student preferred.
• Relevant coursework, labs, research, co-op, internship, or project experience in AI/ML, data analytics, statistics, controls, automation, computer vision, or manufacturing is a plus.
• Must be available for 10 weeks during Summer 2027 (May-August 2027) with a graduation date of December 2027 or later
• Be interested in working for Corning, Inc after graduation, if presented with a full-time job opportunity.
• Be willing to work at the posted job location

Required Skills

• Familiarity with engineering, analytical, or scientific methodology, including the ability to design analyses or experiments to develop understanding.
• Programming experience in Python, MATLAB, C/C++, C#, R, or similar language.
• Foundational understanding of data analytics and AI/ML concepts such as data preparation, feature engineering, supervised/unsupervised learning, model training, model evaluation, and visualization.
• Data/statistical analysis skills and ability to interpret results in the context of a real process or business problem.
• Analytical problem-solving skills and curiosity to learn manufacturing processes and digital technologies.
• Ability to build relationships, work in teams, and interact with multiple functions and levels of the organization.
• Excellent verbal and written communication skills; ability to present technical information clearly.
• Results-oriented approach with good organization, follow-through, and willingness to ask questions and learn.

Preferred Skills

• Experience with Python data or machine learning libraries such as pandas, NumPy, scikit-learn, TensorFlow, PyTorch, OpenCV, or similar tools.
• Experience with SQL, data visualization, Power BI, Git, cloud/data platforms, or industrial data systems.
• Exposure to machine vision, image processing, sensor data, industrial cameras, PLC/HMI/SCADA systems, or manufacturing automation.
• Familiarity with process controls, statistical process control, process capability, Six Sigma/DMAIC, or manufacturing quality systems.
• Interest in applying AI/ML responsibly in manufacturing to improve cost, capacity, quality, capability, and decision-making.