FEA Engineer II

Role details

Job Requirements

The FEA Engineer II develops and applies finite element analysis (FEA), nonlinear material modeling, and engineering automation to support footwear development and improve engineering decision-making at Brooks.

This role independently owns well-defined simulation studies, from problem definition and model development through material calibration, validation, result interpretation, and communication of engineering recommendations. The engineer applies established simulation methods, develops and improves models for assigned applications, and contributes to expanding trusted simulation capabilities across footwear development.

Working closely with Design, Materials, Testing, Run Research, and other engineering partners, the engineer translates product and performance questions into technically sound simulation studies and actionable engineering insights. The role also contributes to automation, design exploration, and emerging capabilities that connect physics-based simulation with optimization, machine learning, and AI-enabled design workflows.

Your Responsibilities

Modeling & Simulation (ModSIM)

• Apply established modeling practices and develop or improve material models and simulation methods for assigned footwear engineering applications
• Develop, calibrate, and validate nonlinear material models for footwear materials, including foams, elastomers, polymers, and composite systems using established modeling approaches and validation practices.
• Implement and maintain validated material models across appropriate simulation platforms and solvers such as Abaqus, OptiStruct, and Radioss.
• Define appropriate model assumptions, contacts, boundary conditions, load cases, and solution methods for well-defined nonlinear footwear simulations using established modeling practices.
• Contribute to the development and improvement of digital test methods that reproduce relevant physical tests and enable quantitative simulation-to-test correlation.
• Use experimental data to assess simulation accuracy and identify opportunities to improve material models, boundary conditions, and existing modeling methodology.
• Document modeling assumptions, calibration methods, validation results, applicability, and limitations to enable consistent application and reuse of simulation methods.
• Apply appropriate implicit and explicit finite element methods based on the engineering problem and loading conditions.
• Apply established geometry preparation, meshing, and model-build workflows to efficiently create high-quality finite element models.
• Consult with senior engineers or technical leaders when simulation problems require significant changes to established methods or involve unusually high technical uncertainty.

Footwear Simulation and Engineering Applications

• Own assigned simulation studies and translate engineering questions into actionable product-development recommendations
• Execute FEA and engineering analyses to support footwear development, innovation, and athlete-related engineering projects
• Translate well-defined design and performance questions into appropriate simulation studies, engineering metrics, and measurable engineering outputs.
• Evaluate material, geometry, and structural design alternatives across footwear components, including sockliners, midsoles, outsoles, and plates, using established simulation methods to understand engineering and performance trade-offs and inform design decisions.
• Integrate physical testing and experimental data into assigned simulation studies to assess model accuracy and support engineering conclusions.
• Collaborate with Design, Materials, Testing, Run Research, and engineering teams to execute simulation studies and support footwear performance decisions.
• Clearly communicate actionable findings, engineering implications, assumptions, uncertainty, and model limitations to technical and cross-functional stakeholders.
• Manage assigned simulation activities to deliver technically sound results within agreed project scope and timing.

Simulation Scale, Standardization, and Automation

• Improve simulation efficiency and consistency by contributing to reusable methods, workflows, and engineering tools.
• Contribute to development and refinement of FEA templates, methods, and workflows for recurring footwear simulation applications.
• Reuse and adapt validated material models, simulation methods, and model assets across projects to reduce duplicated engineering effort.
• Develop Python and other engineering automation tools for preprocessing, model generation, simulation execution, post-processing, data analysis, and reporting.
• Automate repetitive or high-volume simulation tasks to improve engineering efficiency, consistency, and throughput.
• Contribute to geometry, material and simulation asset libraries with appropriate documentation and traceability.
• Support the implementation of validated methods across appropriate simulation platforms and product applications.
• Contribute to improve usability of established simulation workflows and tools to support consistent application across assigned projects.
• Share technical learnings and contribute to the adoption of consistent simulation best practices within the engineering team.
• Identify workflow or automation opportunities and collaborate with senior engineers and technical partners on their development and implementation.

AI-Enabled simulation and optimization

• Contribute to next-generation simulation, optimization, and AI capabilities that enable faster design exploration and more efficient virtual product development.
• Apply and evaluate physics-informed machine learning, surrogate-modeling, and other data-driven optimization methods for assigned engineering applications.
• Prepare, evaluate, and integrate validated simulation and experimental data for AI-enabled engineering applications.
• Execute design-of-experiments, parameter studies, optimization studies, and automated design-exploration workflows.
• Support the exploration and evaluation of methods for rapidly evaluating geometry, material, and structural design alternatives while maintaining appropriate physics-based constraints.
• Support the integration of physics-based simulation and validated experimental data into AI-enabled prediction and design workflows.
• Independently execute assigned proof-of-concept studies to assess predictive accuracy, robustness, computational efficiency, and engineering usefulness of AI-enabled methods.
• Collaborate with cross-functional stakeholders to evaluate promising applications for these methods.
• Contribute to transitioning successful technical explorations into documented, validated, and reusable engineering workflows.

Work Experience

• Bachelor's degree in Mechanical Engineering, Applied Mechanics, or a related engineering discipline.
• 5+ years of professional experience developing finite element models using Abaqus, Altair OptiStruct, Radioss, or comparable FEA solvers and preprocessing tools such as HyperMesh, including meshing, contact definition, boundary conditions, and model quality assessment.
• Experience independently developing and executing nonlinear FEA to footwear, sporting goods, soft materials, consumer products, or similarly complex products.
• Experience developing nonlinear material models for foams, elastomers, composites, or other nonlinear material systems.
• Strong understanding of solid mechanics, nonlinear material behavior, contact mechanics, boundary conditions, and interpretation of simulation results.
• Experience connecting material-level behavior to component- and system-level product performance.
• Experience with both implicit and explicit finite-element methods.
• Experience with design optimization, design of experiments, parameter studies, or automated design exploration.
• Experience with material calibration, experimental data interpretation, and simulation-to-test correlation.
• Programming or scripting experience, preferably Python, for engineering automation, data processing, simulation workflow development, or user-defined subroutines.
• Strong analytical, problem-solving, documentation, and cross-functional collaboration skills.
• Ability to translate physical engineering problems into appropriate computational models and clearly communicate results and limitations.

Preferred Qualifications

• Master’s degree in Mechanical Engineering, Applied Mechanics, or a related discipline
• Experience with surrogate modeling, physics-informed machine learning, or other data-driven computational methods.
• Experience developing reusable simulation workflows, material libraries, or automated engineering tools.
• Familiarity with CATIA and 3DEXPERIENCE

Benefits

Brooks is proud to offer a robust benefits package to our employees and their families!

• Benefits- including medical, dental, vision, life and AD&D insurance, disability insurance, HSA and employer contribution, FSA, family & fertility assistance, 401K Savings Plan and match, employee assistance program, and transportation assistance.
• Paid Time Off- Brooks offers generous time off including five weeks of paid time off, eleven paid holidays, paid sick and parental leave.
• Bonus- in addition to base pay, Brooks employees may also be offered an annual bonus based on company performance.
• Perks- including product discounts, employee recognition, fitness discounts, volunteer and donation benefits.
• Location- You will spend 4 days per week in our Seattle offices, as we believe our organization flourishes when connections, collaboration, creativity, problem-solving, and celebrations happen in person.

Compensation

The pay range for this position, based out of the Brooks Seattle HQ, is $104,217 - $156,325 per year. Base pay offered will vary depending on job-related knowledge, skills, and experience.