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Corning

Sr. Software System Engineer

Corning
Shanghai, SH, CN, 200031Full TimeSeniorPosted Today

Requisition Number: 75770

 

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 Manufacturing, Technology and Engineering division (MTE) is recognized as the leader in engineering excellence & innovative manufacturing technologies by providing diverse skills to Corning’s existing & emerging businesses.

We anticipate & provide timely, valued, leading edge manufacturing technologies and engineering expertise.  We partner with Corning’s businesses and the Science & Technology division. Together we create and sustain Corning’s manufacturing as a differential advantage.

Key Responsibilities

Industrial Data Governance and Feature Engineering

Build standardized data processing pipelines for multi-source industrial data, including process, quality, equipment, and energy-related data. This includes timestamp alignment, data cleaning, anomaly handling, lag analysis, and feature engineering, providing a solid data foundation for modeling and business analysis.

Industrial Modeling and Intelligent Diagnosis

Design and develop algorithms for industrial scenarios, including time-series forecasting, multivariate process modeling, anomaly detection, fault diagnosis, and soft sensing. Apply quality tracing and causal analysis methods to identify key influencing factors and support process optimization and quality improvement.

Industrial Problem Abstraction and Optimization

Abstract real-world manufacturing problems into decision variables, constraints, and optimization objectives. Collaborate with domain experts to identify true business constraints, hidden rules, and data boundaries. Based on this, develop solutions using traditional machine learning and deep learning methods, while continuously improving solving efficiency, stability, interpretability, and scalability.

Large Model and AI Application Deployment

Explore and apply cutting-edge large models (e.g., LLMs, VLMs) and related technologies (e.g., RAG, fine-tuning, LoRA, post-training) to address practical challenges in intelligent manufacturing, such as production efficiency, cost reduction, quality improvement, and energy optimization, and create measurable business value.

Industrial Agent Design and Development

Define functions, design system architecture, and develop algorithmic solutions for industrial AI agents. Be responsible for feasibility validation, model training, deployment, and practical application, promoting deep integration of AI agents with industrial business workflows.

Technology Research and Innovation

Track and study the latest developments in large models, AI agents, and industrial AI technologies relevant to manufacturing scenarios. Explore new technologies and methodologies for manufacturing applications and drive continuous innovation.

Cross-functional Collaboration and On-site Support

Work closely with process, production, equipment, and IT teams to support solution validation, system integration, and large-scale deployment. Travel to factories when necessary for on-site investigation, implementation, and delivery support.

Experiences/Education - Required

Education

Master’s degree or above in Mathematics, Statistics, Automation and Control, Chemical Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, or other related STEM fields.

Project Experience

At least 5 years of relevant work experience, with hands-on project experience in industrial scenarios such as equipment condition monitoring, process parameter optimization, feedback control, and product quality monitoring. Experience in lag tracing, correlation/causal analysis, and key factor identification and validation is preferred. Candidates should be capable of independently or jointly leading system design, coding, debugging, and project delivery.

Industrial System Knowledge

Familiarity with industrial systems and data environments such as DCS, MES, LIMS, SCADA, and OPC, with a solid understanding of industrial business processes and data flows.

Algorithm Expertise

Strong knowledge of machine learning methods and proficiency in two or three deep learning approaches, such as NN, CNN, RNN, LSTM, GRU, and Encoder/Decoder architectures, with solid algorithm design and modeling capabilities.

Large Model Experience

Practical experience applying large model technologies in real-world business scenarios. Hands-on experience with at least one or two of the following: RAG, fine-tuning, and LoRA. Experience with large models in industrial scenarios is a strong plus.

Multimodal Data Processing

Understanding of multimodal industrial data processing workflows, with experience in preprocessing, feature extraction, and modeling of text, image, and audio data.

Programming and Engineering Skills

Proficiency in Python for algorithm development, modeling, and data processing. Experience with C/C# development is a plus. Familiarity with data structures, algorithm complexity analysis, and software engineering best practices is required.

Engineering Delivery Capability

Familiarity with Git, unit testing, performance testing, and code review processes. Experience in SQL, API/interface design, and algorithm service deployment, with the ability to take algorithms from prototype to production-grade deployment.

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at accommodations@corning.com.

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Sr. Software System Engineer at Corning