Senior Explicit Dynamics Engineer

About Us

Fortune Brands began its journey as a publicly traded company (NYSE: FBHS or "Fortune Brands Home & Security, Inc.") in 2011, as a successful spin-off from Fortune Brands, Inc. Since then, we have grown organically and through acquisitions, and have delivered strong financial performance. We have also proven our resilience and execution excellence. We outperformed and expanded in our categories through the housing market recovery, and executed our strategies through global disruptions, while refining our portfolio for the future.

On December 14, 2022, we completed the separation of our Cabinets business, enabling us to pursue our unique and exciting path for accelerating growth and productivity.

Today, we are a new company: Fortune Brands Innovations, Inc. (NYSE: FBIN). We are focused on driving our brand, innovation and channel leadership, and winning in supercharged categories.

Why work with us?

You will gain the flexibility to balance your life at every stage with Total Rewards that support your physical, emotional, and financial well-being. We also support an inclusive and diverse culture where everyone is encouraged and empowered to be authentic, and where our differences and unique perspectives are a key strength

In Fortune Brands Innovation, Inc. We are seeking an experienced Senior Explicit Dynamics Engineer

As the Senior Explicit Dynamics Engineer, you will be the technical lead for simulating and validating high-impact, transient events across a diverse product portfolio—ranging from padlocks and door hardware to composite components. Your mission is to build robust, predictive models that replace physical drop, crash, and impact tests with high-fidelity virtual simulations.

• Design and execute explicit dynamic simulations using Explicit Dynamics solvers.
• Develop parametric simulation templates and reusable playbooks that standardize virtual testing across product families.
• Calibrate complex nonlinear material models, including rate-dependent plasticity, hyperelasticity, and viscoelasticity, using lab-generated coupon data.
  • Integrate AI/ML techniques into your workflow to:
  • Build surrogate models for rapid design screening. 
  • Apply active learning to identify the most informative physical tests.
  • Quantify uncertainty and improve model robustness. o Automate simulation pipelines using Python and APDL and LS DYNA, enabling scalable meshing, parametric sweeps, and post-processing.
• Collaborate with lab technicians to ensure high-quality data acquisition and traceability for model correlation.
• Lead the correlation effort between virtual and physical tests.
• Mentor engineers and foster a culture of technical excellence, creativity, and continuous learning.
• Champion innovation, bringing a playful and curious mindset to problem-solving and simulation storytelling.

• B.S. degree in Engineering (Mechanical preferred) from an accredited university
• Minimum of 8 years of hands-on experience in explicit dynamics simulation, including impact, drop, crash, and transient load scenarios.
• Proficiency in explicit solvers such as LS-DYNA, Abaqus/Explicit, or Radios, with demonstrated ability to model high-strain-rate events and contact interactions.
• Deep understanding of nonlinear material behavior, including rate-dependent plasticity, hyperelasticity, and viscoelasticity, especially for polymers and composites.
• Experience in developing and calibrating complex material models using coupon test data and integrating them into simulation workflows.
• Strong command of Python for automating simulation tasks such as meshing, parametric sweeps, post processing, and report generation (e.g., using PyAnsys, Matplotlib).
• Implementing active learning strategies to identify the most informative physical tests.
• Supporting uncertainty quantification and sensitivity analysis in dynamic simulations.
• Ability to work with multi-physics environments, integrating structural, thermal, and fluid effects when needed.
• Excellent communication skills and ability to collaborate with cross-functional teams including lab technicians, data scientists, and product engineers.
• Strong documentation skills to contribute to credibility reports, correlation matrices, and simulation playbooks.