Sr Engineer / Lead Engineer - Paint Simulation

Sponsorship : GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE.  DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.  Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office four times per week or other frequency dictated by the business. What You’ll Do Perform Electrocoat thickness prediction, Fluid Access & Drainage study and Oven bake simulation studies Perform special simulation studies like Flow Behavior Analysis for chronic process problems in paint shops Provide and implement continuous process improvement ideas within the team Collaborate with stakeholders to understand business challenges in the CFD space and solve them using API based customization and AI methodologies. Stay updated on advancements in neural networks, multi-physics simulations, surrogate modelling and physics-informed learning techniques. Achieve KPI metrics like 100% First Time Quality, 100% On time delivery Represent paint simulation in the appropriate forums. Participate in global product development council & technical team meetings Sound knowledge in StarCCM+ / ALSIM, Teamcenter, AutoCAD, MS Office applications. Sound knowledge in any of the CAE/FEA tools Hypermesh 2025, ANSA etc. Your Skills & Abilities (Required Qualifications) Bachelor’s degree in Mechanical / Aeronautical/ Chemical/ Automobile Engineering discipline with a Specialization in Thermal Engineering preferred. 6+ years of Paint process & simulation experience from Automotive OEMs / Engineering Organizations. Good knowledge of fluid mechanics, heat transfer and computational fluid dynamics concepts. Experience in data handling (large-scale CFD datasets) and feature engineering(feature extraction from flow fields like velocity, pressure, turbulence quantities). Good knowledge of complete automotive paint shop processes, materials and facilities preferred Good knowledge in AI technologies & algorithms. Experience with ML frameworks like Pytorch, TensorFlow preferred Good understanding of the GVDP, GLP, Quality Chain, DFMEA-PFMEA preferred Sound knowledge of OpEx tools, Six sigma and Red X methodologies Knowledge of surrogate modeling, reduced-order modeling (ROMs), and regression techniques. Experienced in working with multiple interfaces to deliver the results. Good verbal and written communication skills. Good Problem solving & analytical skills. Good coding skills on process automation and business intelligence tools (C/C++, Java, VB script, Python, Power BI etc.,) Ability to work with intercultural & multi-disciplinary teams to achieve enterprise goals High level of integrity, ability to deal with ambiguity, takes initiative/self-directed 



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