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Corning

Specialty glass, ceramics, and tech components

Senior Engineer - Machine Learning

Applied Machine LearningUpdated on Nov 14
Full-timeDurham, NC, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related technical discipline with two or more years of relevant applied experience; alternatively, a master's or doctoral degree with substantial applied project, capstone, thesis, internship, or research experience.
  • Applied experience using machine learning methods for classification, regression, clustering, forecasting, or related analytical problems.
  • A strong foundation in statistics, data science, model evaluation, and data-driven problem solving.
  • Experience in at least one area of machine learning, deep learning, computer vision, or large language models.
  • Proficiency in Python and working knowledge of object-oriented programming.
  • Experience with at least one major machine learning framework or data-analysis library, such as PyTorch, TensorFlow, Pandas, Polars, DuckDB, or PySpark.
  • Familiarity with Git and version-control practices.
  • Ability to understand an engineering or business problem, select appropriate analytical methods, and explain the rationale behind the approach.
  • Ability to communicate technical findings effectively to technical and nontechnical stakeholders.
  • Ability to work in the United States without current or future immigration sponsorship and meet export-control eligibility requirements.

Responsibilities

  • Partner with manufacturing, engineering, and business stakeholders to understand technical problems and develop machine learning or AI solutions that deliver practical business impact.
  • Perform exploratory and targeted data analysis; prepare data, select appropriate methods, develop models, evaluate results, and clearly communicate recommendations.
  • Develop machine learning solutions for classification, regression, clustering, predictive maintenance, condition-based maintenance, process modeling, computer vision, or inspection-system applications.
  • Develop and support large language model-integrated applications, including Model Context Protocol and retrieval-augmented generation-based process, equipment, or knowledge assistants.
  • Build predictive and classification models and support deployment into production environments, including on-premise systems, servers, cloud, or edge devices.
  • Configure, manage, and troubleshoot machine learning application environments, data workflows, and deployment infrastructure as needed.
  • Document technical approaches, model development, validation, results, and recommendations through reports and presentations.
  • Collaborate across multidisciplinary teams and contribute to identifying, scoping, and developing new machine learning opportunities.

Desired Qualifications

  • Experience with predictive maintenance, condition-based maintenance, manufacturing analytics, equipment data, process modeling, or industrial-data applications.
  • Experience with computer vision, inspection systems, OpenCV, HALCON, convolutional neural networks, recurrent neural networks, YOLO, or related techniques.
  • Familiarity with large language model application development, Claude Code, OpenCode, Codex, Model Context Protocol, retrieval-augmented generation, agentic AI frameworks, or related tools.
  • Experience with Linux, CUDA, GPU computing, NVIDIA edge-device environments, cloud platforms, or production machine learning deployment.
  • Experience with MATLAB, C#, R, LabVIEW, C++, C, SQL, ETL workflows, data extraction, data cleansing, or data manipulation.
  • Experience with Streamlit, Dash, Flask, Blazor, Power BI, or other application-development, visualization, or reporting tools.
  • Familiarity with CI/CD pipelines and cloud-based storage or compute environments such as AWS or Microsoft Azure.
  • Experience transitioning proof-of-concept machine learning work into deployed production applications.
  • Experience identifying machine learning opportunities, shaping technical proposals, or building stakeholder support for data-driven solutions.

About the Company

Corning

Specialty glass, ceramics, and tech components

Corning develops and manufactures specialty glass, ceramics, and related components for a range of industries. Its engineered glass and ceramic materials are produced and integrated into devices and systems such as smartphone screens, high‑performance displays, optical networks, automotive emissions controls, and life‑science equipment. The company differentiates itself with a broad portfolio across multiple markets, material science expertise, reliable supply, and end‑to‑end components and systems. Its goal is to help customers achieve performance and reliability by providing durable, high‑quality materials and connected solutions that scale with growing demand.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Corning, NY
Founded
1851

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