Machine Learning Modeling Engineer

Corning•City of Corning, NY

1d•$91,311 - $125,553•Onsite

About The Position

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.

Requirements

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 TensorFlow.
Familiarity with generative AI tools and frameworks.
Strong mathematical and programming skills using Python.
Comfortable working in Windows, Linux parallel processing cluster environments, and Databricks.
Strong communication skills and ability to work effectively with scientists, engineers, and technical stakeholders.
Ability to work independently and in a team environment while managing multiple priorities.

Nice To Haves

Background in time series, computer vision, natural language processing, physics-informed neural networks, or uncertainty quantification.
Track record of journal or conference publications in relevant technical fields.
Knowledge of emerging technologies and algorithms in AI/ML.
Experience with physics-based modeling and ability to analyze, optimize, and debug scientific code.
Experience building scalable data analytics solutions.
Experience with Databricks Workflows, Delta Lake, and data governance frameworks.
Foundation in software design principles and ability to design and develop applications as needed.
Demonstrated ability to support multiple projects in a fast-paced technical environment.
Strong motivation, attention to detail, and commitment to advancing beyond the current state.

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.