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Global OEM brand and Bangalore location increase applicant density despite niche CFD/ML specialization.
Highly domain-specific automotive paint process and CFD expertise reduces cross-industry transferability.
Mandatory 6+ years, domain-specific CFD tools, and ML framework expertise create strict screening.
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Lead paint simulation studies including Electrocoat thickness prediction, fluid access and drainage, and oven bake simulations to improve paint shop processes.
Implement continuous process improvements and collaborate with stakeholders using API customization and AI methods to solve CFD-related business challenges.
Represent paint simulation in technical forums, achieve key performance indicators like 100% First Time Quality and On Time Delivery, and apply expertise in CFD and AI technologies.
Bachelor’s degree in Mechanical, Aeronautical, Chemical, or Automobile Engineering (Thermal Engineering specialization preferred).
6+ years of paint process and simulation experience in Automotive OEMs or engineering organizations.
Proficiency in CFD concepts, paint shop processes, AI/ML frameworks (e.g., PyTorch, TensorFlow), and simulation tools (StarCCM+, ALSIM, Hypermesh, ANSA).
Work arrangement: Hybrid with the expectation to report to office four times per week; GM does NOT provide immigration sponsorship.
Experienced in automotive paint shop simulation and able to integrate CFD with AI and process automation for problem-solving.
Skilled in handling large-scale CFD datasets, surrogate/reduced-order modeling, and multi-disciplinary collaboration.
Demonstrates strong knowledge of quality and process improvement frameworks like GVDP, GLP, DFMEA/PFMEA, Six Sigma, and Red X methodologies.