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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Engineer, Machine Learning - **Company:** Corning - **Location:** Durham, NC, United States - **Experience:** Expert - **Salary:** $91,311.0 - $125,553.0 - **Contract:** Internship / Graduate position - **Skills:** C (Programming Language), Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, C Sharp (Programming Language), C++ (Programming Language), Cloud Storage, Cluster Analysis, Nvidia CUDA, Data Cleansing, Extract Transform Load (ETL), Data Mining, Linux, R (Programming Language), General-Purpose Computing on Graphics Processing Units, Python (Programming Language), LabVIEW, MATLAB, Machine Learning, Object-Oriented Software Development, OpenCV, Power BI, Tensorflow, Smart Devices, Software Engineering, SQL Databases, Data Processing, Pytorch, Blazor, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Claude Code, Deep Learning, Model Validation, Convolutional Neural Networks, Agentic-AI, Git, Pandas, Pyspark, Infrastructure Automation Frameworks, Information Technology, Data Analytics, Tools for Reporting, Model Context Protocol, Streamlit Framework, Software Version Control, Recurrent Neural Networks - **Published:** October 20, 2026 - **Apply:** https://corningjobs.corning.com/talentcommunity/apply/1441569000/?locale=en_US ## About the Role * Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related technical discipline with two or more years of relevant applied experience; or 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 * 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 both technical and nontechnical stakeholders * Ability to work in the United States without current or future immigration sponsorship and meet export-control eligibility requirements Experiences/Education - Desired * 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 LLM 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 ## Description * 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 LLM-integrated applications, including MCP- and RAG-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 identification, scoping, and development of new machine learning opportunities