Senior LLM and Materials Informatics Scientist

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Company: Freudenberg Nonwovens, LP

Location: Plymouth, MI 48170

Description:

Responsibilities
  • Implement and fine-tune state-of-the-art Large Language Models for various material, product and process design applications, focusing on performance and accuracy.
  • Implement Retrieval-Augmented Generation (RAG), LLM agents etc. to enhance the capabilities of Large Language Models.
  • Lead the incubation of new initiatives, architect scalable solutions, and drive strategic technology choices to develop and deliver LLM enhanced materials informatics capabilities
  • Leads activities in generative AI and physics-informed machine learning for product, formulation, material/process discovery and design.
  • Develop advanced data-driven and physics-based models to guide and accelerate the development of products, materials and processes for sustainable solutions and new mobility applications.
  • Analyze and interpret materials data using advanced statistical and data mining techniques.
  • Propose, execute and defend project concepts; collaborate and plan experimental campaigns for model development, validation and deployment with Freudenberg Business Groups.
Qualifications
  • PhD or equivalent experience in materials science, chemistry, chemical engineering, physics, mechanical engineering, or related fields.
  • Minimum 5 years of experience in computational methods (Ab Initio / MD / FEA / CFD / Multi scale / Multi physics / cheminformatics / materials informatics) for material or product design optimization (e.g., Bayesian optimization), either in industry or academia.
  • Experience with Generative AI, AI/ML tools for accelerating physics-based simulations.
  • Develop scalable Generative AI solution frameworks and exposure to deployment strategies
  • Experience with integrating Generative AI tools such as OpenAIs GPT models, Metas Llama models, Hugging Face, etc. in material / product design solutions.
  • Experience with applying Generative AI for extracting data from patents, publications, reports and data sheets.
  • Proficiency in programming languages like Python, Julia, C/C++, and familiarity with SQL, MySQL, MongoDB, Flask, Azure, or other cloud technologies.


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