Senior Design Engineer (Kingsport, TN, US, 37660)
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Before you apply
LocationKingsport, TN, US, 37660
Work modeon-site
Typefull-time
SenioritySenior
Experience1–5 yrs
Company size10,000+ people
First seenOct 26, 2026 · 1w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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
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
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
Ability to work with structured and unstructured datasets
Ability to translate technical and business needs into practical digital solutions
Strong written and verbal communication communication skills
Ability to work effectively in multidisciplinary teams
Academic or industry experience that combines materials science and computational or AI disciplines
Experience applying AI, machine learning, or advanced analytics to scientific, engineering, manufacturing, or product development challenges
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
Skills
Python
machine learning
AI
Large Language Models (LLMs)
prompt engineering
retrieval-augmented generation (RAG)
vector databases
embeddings
knowledge retrieval systems
Moldflow
Ansys
Comsol
Simulink
Benefits
Health insurance
Dental coverage
Prescription drug
Health savings account
Vision
Life insurance
Critical illness
401(k)
Company match
Retirement contribution
Paid holidays
Paid time off
Paid vacation
Parental leave
Employee assistance program
Mentorship
Leadership programs
About the company
Founded in 1920, Eastman is a global specialty materials company that produces a broad range of products found in items people use every day. With the purpose of enhancing the quality of life in a material way, Eastman works with customers to deliver innovative products and solutions while maintaining a commitment to safety and sustainability. The company’s innovation-driven growth model takes advantage of world-class technology platforms, deep customer engagement, and differentiated application development to grow its leading positions in attractive end markets such as transportation, building and construction, and consumables. As a globally inclusive company, Eastman employs approximately 13,000 people around the world and serves customers in more than 100 countries. The company had 2025 revenue of approximately $8.8 billion and is headquartered in Kingsport, Tennessee, USA. For more information, visit www.eastman.com.
Responsibilities
About the role
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.
Nice to have
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.
Benefits
Your total rewards go far beyond a competitive salary. When you join Eastman, you gain access to an exceptional suite of programs designed to protect your health, grow your wealth, and fuel your career.
Compensation & Incentives
• Base pay plus performance-based incentive opportunities that let you share in our success.
Health & Wellness
• Comprehensive medical, prescription-drug, and dental coverage—paired with a Health Savings Account option to help you save tax-free dollars for care today or in the future.
• A robust menu of voluntary benefits—including vision, optional life, critical-illness protection, and more—so you can tailor coverage to fit your life.
• Holistic wellness support: financial-planning tools, family-building assistance (adoption, pregnancy, and fertility resources), parental leave, and confidential Employee Assistance Program counseling.
Retirement & Financial Strategies
• 401(k) with a company match—plus an additional annual retirement contribution from Eastman to accelerate your long-term savings.
Time Away
• Eleven paid holidays, one personal day, paid time off, and paid vacation to recharge, celebrate, or handle life’s moments.
Growth & Development
• Access to mentorship, learning resources, and leadership programs that empower you to thrive in your current role and chart the next steps in your career.
At Eastman, we invest in the whole you—so you can bring your best self to work every day and build a future you’re proud of.
Legal
Eastman Chemical Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, pregnancy, veteran status or any other protected classes as designated by law.
Eastman is committed to creating a powerfully engaged workplace, where everyone can contribute to their fullest potential each day.
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