Simulation R&D Engineer

Your Job

We are seeking a highly motivated engineer to develop and apply artificial intelligence and machine learning (AI/ML) techniques to accelerate structural and electrical simulations. This role bridges product development, finite element analysis (FEA), signal integrity (SI) analysis, and AI modeling, enabling faster and smarter product design.

You will work closely with domain experts in simulation and data science to explore physics-informed AI models and hybrid simulation workflows (e.g., reduced‑order modeling, surrogate modeling, or neural operators) for real‑world structural applications.

At Molex, we create connections for life by enabling technologies that transform the future and improve lives. With a presence in more than 40 countries, we offer a complete range of connectivity products, services, and solutions across various industries, including data communications, medical, industrial, automotive, and consumer electronics.

Our Datacom and Specialty Solutions (DSS) team specializes in providing high‑speed connector solutions essential for building reliable communications equipment, catering to telecommunications, datacom, hyperscalers, cloud, data center, and storage applications. We continue to innovate to meet the demands of next‑generation markets.

• Develop, implement, and validate next‑generation simulation frameworks that leverage data‑driven and physics‑based approaches to accelerate structural and multi‑physics analyses.
• Integrate physics‑informed or reduced‑order models into existing FEA workflows (e.g., Abaqus, LS‑DYNA, ANSYS Workbench) to enhance speed and scalability.
• Build and calibrate surrogate models that accurately approximate high‑fidelity simulations while maintaining minimal accuracy loss.
• Automate data generation and management pipelines from FEA results to support model training, validation, and continuous improvement.
• Analyze and balance trade‑offs among model fidelity, computational efficiency, and generalization performance for different applications.
• Evaluate and deploy emerging AI‑for‑simulation technologies (e.g., Altair Physics
  
  AI, Ansys SimAI) to accelerate structural, thermal, and electrical co‑simulation and design optimization.
• Design and enhance automated optimization workflows that couple FEA and signal integrity simulations (e.g., using Mode Frontier, ANSYS OptiSLang, or equivalent platforms).
• Document, publish, and communicate findings to promote adoption of advanced simulation methodologies across engineering teams.

• B.S. Degree in Mechanical Engineering, Computer Science, Data Science, or a related field.
• Strong foundation in solid mechanics, finite element methods (FEM), and numerical modeling for structural and multi‑physics applications.
• Hands‑on experience with one or more major FEA tools (e.g., Abaqus, ANSYS Workbench, LS‑DYNA), including setup, analysis, and interpretation of results.
• Proficient in Python programming, with experience in numerical and scientific computing libraries such as Num Py, Sci Py, and related tools.
• Experience with data preprocessing, model training, and validation workflows, including handling simulation datasets and building data pipelines for AI/ML applications.
• Excellent communication skills, with the ability to convey complex technical concepts effectively to interdisciplinary teams and stakeholders.

• M.S. or Ph.D. in Mechanical Engineering, Computer Science, Data Science, or a related field, with a strong focus on computational modeling or AI applications.
• Experience with advanced machine learning architectures, such as Physics‑Informed Neural Networks (PINNs) etc., for physics‑based modeling.
• Prior exposure to AI‑driven simulation frameworks such as Physics
  
  AI, SimAI, or equivalent platforms.
• Background in reduced‑order modeling (ROM), surrogate modeling, or Bayesian calibration, with experience in integrating these approaches into simulation workflows.
• Familiarity with CAD/CAE automation and data pipelines for simulation‑driven design and optimization.
• Proven ability to translate research concepts into practical, deployable solutions in…