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.
Our Team
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.
What You Will Do
- 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 PhysicsAI, 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 ModeFrontier, ANSYS OptiSLang, or equivalent platforms).
- Document, publish, and communicate findings to promote adoption of advanced simulation methodologies across engineering teams.
Who You Are (Basic Qualifications)
- 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 NumPy, SciPy, 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.
What Will Put You Ahead
- 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 PhysicsAI, 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 engineering or simulation contexts.
- Strong record of technical contributions, such as peer-reviewed publications, patents, or conference presentations.
For this role, we anticipate paying $90,000 - $120,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recrui