Senior Design Engineer

Responsibilities

This role combines expertise in materials science, polymer science, data science, and artificial intelligence to build the data foundation, machine learning models, and AI-enabled tools that support Eastman's Specialty Plastics business. The successful candidate will leverage Eastman's proprietary material, processing, application, and customer knowledge to develop digital solutions that accelerate product development, improve technical decision-making, enhance customer support, and create differentiated business value. This position is located onsite at our headquarters in Kingsport, TN.

Responsibilities:
•    Build, expand, and maintain proprietary data assets including failure analysis data, processing parameters, material properties, characterization results, application performance data, and customer project information.
•    Establish data collection, documentation, and governance standards that improve the quality, consistency, and usability of technical data across the organization.
•    Work with Eastman's IT, Digital, and Data Science teams to develop secure, scalable, and reliable data infrastructure while protecting company and customer information.
•    Develop, deploy, maintain, and continuously improve AI-powered tools that support technical workflows including failure analysis, design-for-manufacturability (DFM), material selection, processing optimization, troubleshooting, and root-cause analysis.
•    Build and maintain AI assistants and knowledge systems that enable technical and commercial teams to rapidly access information and answer routine technical questions.
•    Develop machine learning models that combine historical material, processing, application, and Moldflow simulation data to predict performance, identify failure risks, and recommend optimization opportunities.
•    Develop AI-enabled tools that support application development by recommending materials, processing conditions, design guidelines, and application solutions using Eastman's proprietary technical knowledge.
•    Partner with scientists, engineers, application development teams, manufacturing personnel, commercial teams, and data scientists to identify opportunities where AI and machine learning can improve productivity and technical outcomes.
•    Evaluate emerging AI technologies and implement practical solutions that enhance innovation, knowledge management, and business performance.

Qualifications

Education and Experience:
•    PhD in Chemical Engineering, Materials Science, Polymer Science, Computer Science, Data Science, Computational Engineering, or a related field with 1-2 years of relevant postdoctoral or industrial experience; or
•    Master's degree in a related field with 4-5 years of relevant industry experience in material informatics, machine learning, artificial intelligence, data science, or related technical disciplines.
•    Academic or industry experience that combines materials science and computational or AI disciplines is highly desirable.

Required Skills:
•    Strong programming skills, particularly in Python and modern data science environments.
•    Experience developing, validating, and deploying machine learning models and AI applications.
•    Experience with Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), vector databases, embeddings, and knowledge retrieval systems.
•    Strong data management, analytical, and problem-solving skills with the ability to work with structured and unstructured datasets.
•    Ability to translate technical and business needs into practical digital solutions.
•    Strong written and verbal communication skills and ability to work effectively in multidisciplinary teams.

Preferred Skills and Experience:
•    Experience applying AI, machine learning, or advanced analytics to scientific, engineering, manufacturing, or product development challenges.
•    Experience building AI assistants, copilots, agent-based systems, or decision-support tools.
•    Experience integrating simulation outputs, such as Moldflow, Ansys, Comsol, Simulink results, with machine learning models.
•    Understanding of polymer processing, materials characterization, manufacturing, product development, or application engineering.
•    Experience in specialty plastics, polymers, advanced materials, specialty chemicals, or manufacturing industries.
•    Experience developing predictive models using limited, incomplete, or real-world industrial datasets.

Preferred Candidate Profile:
The ideal candidate combines strong AI and machine learning expertise with an understanding of materials science and engineering. They are passionate about developing proprietary data assets, AI-powered technical tools, and digital solutions that accelerate innovation, improve technical productivity, and create competitive advantage for Eastman's Specialty Plastics business.