Machine Learning Modeling Engineer

Machine Learning Modeling Engineer

** Date:
** Aug 10, 2026

*
* Location:

** Corning, NY, US, 14831

** Company:
** Corning

Requisition Number: 76873

** The company built on breakthroughs. ​ *
* ** Join us.​ *
* Corning is one of the world's leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what's possible.  ​ 

How do we do this? With our people. They break through limitations and expectations - not once in a career, but every day. They help move our company, and the world, forward. ​ 

​At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.​  

Come break through with us. 

Corning's businesses are ever-evolving to best serve our customers, industries, and consumers. Today, we accelerate and transform life sciences, mobile consumer electronics, optical communications, display, automotive, and solar markets. We are changing the world with:

+ Trusted products that accelerate drug discovery, development, and delivery to save lives

+ Damage-resistant cover glass to enhance the devices that keep us connected

+ Optical fiber, wireless technologies, and connectivity solutions to carry information and ideas at the speed of light

+ Precision glass for advanced displays to deliver richer experiences

+ Auto glass and ceramics to drive cleaner, safer, and smarter transportation

+ Solar polysilicon, wafers, and innovative photovoltaic modules, enabling low-cost solar energy solutions

** THIS POSITION IS LOCATED IN CORNING, NY*
* ** Role Purpose*
* The Machine Learning Modeling Engineer develops advanced machine learning and AI solutions to support product and process design, development, and innovation across Corning. This role provides data analytics, modeling, and software development support to help solve critical technical problems, improve decision making, and create novel computational methods that strengthen Corning's competitive advantage.

** Key Responsibilities*
* - Develop advanced machine learning, deep learning, and generative AI models in support of research, engineering, and product development initiatives.

- Partner with scientists, engineers, and business stakeholders to define project requirements, identify opportunities for analytics and machine learning, and translate technical needs into effective modeling solutions.

- Prepare data, perform exploratory data analysis, and develop, test, and refine machine learning models to support Corning products at different stages of development.

- Interpret modeling and analytical results in research, engineering, and business context and clearly communicate findings, implications, and recommendations to stakeholders.

- Support software development and computational modeling efforts related to data analytics, machine learning, and scientific computing.

- Research and improve applicable technologies while helping expand Corning expertise in emerging AI/ML methods and related technical areas.

- Write and maintain technical documentation, provide user training as needed, and mentor new engineers and scientists.

- Support multiple projects and collaborate across teams to deliver effective and scalable analytics and machine learning solutions.

** Experiences/Education - Required*
* - MS or PhD required in engineering, computer science, mathematics, statistics, or related discipline, with specialization in machine learning and artificial intelligence.

- Background in one or more scientific disciplines such as physics, chemistry, or engineering required.

- Experience preparing data for machine learning and performing exploratory data analysis independently.

- Deep knowledge of machine learning techniques, including traditional machine learning, deep learning, convolutional neural networks, recurrent neural networks, generative models, and reinforcement learning algorithms.

- Practical experience using machine learning and deep learning frameworks such as PyTorch or Tensor Flow.

- Familiarity with…