CAE Engineer – Piston Structures & Durability

General Motors•Warren, MI

8h•Hybrid

About The Position

We are seeking a CAE Engineer to support piston structures and durability within Global Virtual Engineering. This role converts engineering questions, requirements, and failure modes into physics-based analysis and clear design decisions. The engineer will independently execute moderate-scope work, resolve non-routine technical issues, and partner with program teams, design-release engineers, suppliers, and other virtual-analysis specialists. The role helps GM make earlier, higher-confidence decisions on piston and cranktrain hardware by combining structural CAE, engineering judgment, risk-based evaluation, and reusable capability development. The successful candidate will contribute to production program support while improving standard work, automation, and the team’s ability to detect and reduce design risk.

Requirements

Bachelor’s degree in Mechanical Engineering, Automotive Engineering, Aerospace Engineering, Materials Engineering, or a related technical discipline; equivalent relevant experience may be considered.
Professional experience applying CAE, FEA, or comparable engineering simulation methods to structural, durability, thermal-structural, or related mechanical problems.
Demonstrated ability to work independently with limited guidance, exercise sound engineering judgment, and determine an appropriate course of action within established procedures and practices.
Experience defining analysis inputs and boundary conditions, evaluating model quality, interpreting results, and communicating limitations, uncertainty, and recommendations.
Ability to identify and resolve non-routine technical problems and manage moderate-scope work through completion.
Strong written and verbal communication skills, including the ability to explain technical conclusions to both engineering specialists and broader program audiences.
Ability to collaborate effectively with cross-functional teams, suppliers, and customers while maintaining accountability for quality, timing, and follow-through.

Nice To Haves

Master’s or Ph.D. degree in Mechanical Engineering, Automotive Engineering, Aerospace Engineering, Materials Engineering, or a related technical discipline.
Experience with piston structures, piston pins, connecting rods, cranktrain components, engine durability, or related powertrain hardware.
Experience with tools such as Abaqus, HyperMesh, FLARE, AVL EXCITE, or comparable pre-processing, solving, and post-processing environments.
Knowledge of piston failure modes and performance topics such as safety factors, thermal loading, bore distortion, skirt contact/scuffing, land clearance, piston noise, pin behavior, or fatigue.
Experience with DFMEA, risk-based evaluation planning, design variation/sensitivity studies, qualification evidence, or virtual–physical correlation.
Experience developing or maintaining engineering standard work, analysis procedures, Excel/VBA tools, Python/MATLAB scripts, automation, or reusable engineering workflows.
Experience working with production programs, supplier technical issues, warranty/field investigations, or design changes under timing pressure.
Experience applying artificial intelligence or machine learning to engineering workflows—such as surrogate modeling, reduced-order modeling, design-space exploration, optimization, or predictive analytics—and using design synthesis methods to generate, evaluate, and down-select component or system concepts.

Responsibilities

Lead piston structural and durability evaluations from problem definition through recommendation, including load definition, model setup, analysis execution, post-processing, interpretation, and technical reporting.
Assess piston and related component performance across thermal, mechanical, inertia, pressure, bore-distortion, clearance, and other relevant operating conditions.
Use appropriate CAE fidelity for the engineering decision: fast screening methods for broad option spaces and higher-fidelity models for critical risk retirement and design release decisions.
Diagnose non-routine issues, perform sensitivity and variation studies, identify likely failure mechanisms, and recommend practical design or analysis improvements.
Connect analysis to requirements, DFMEA failure modes, detection/prevention methods, and qualification evidence so that virtual work directly supports risk reduction.
Prepare concise, traceable analysis reports and decision packages for program teams, DREs, suppliers, leadership reviews, PPDR/PRTS support, and warranty or field investigations as needed.
Maintain and improve piston-analysis standard work, procedures, templates, macros, and reusable data practices; identify opportunities to improve cycle time, physics, repeatability, and first-time quality.
Develop automation and capability improvements using appropriate tools such as Python, MATLAB, Excel/VBA, or comparable scripting and post-processing methods.
Support benchmarking and method development, including comparison of alternative tools, model fidelity, correlation evidence, and emerging virtual-engineering practices.
Share knowledge and coach developing engineers or technical partners on analysis methods, standard work, interpretation, and quality expectations.
Collaborate across piston, rings, connecting-rod, cranktrain, lubrication/tribology, materials, testing, design, and program organizations to deliver customer-focused outcomes.