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 three times per week or other frequency dictated by the business.
The Role
Senior Engineer / Lead Engineer – AI CFD will Drive AI innovation in CFD domain. Execute end-to-end projects from idea to deployment, applying AI/ML knowledge to build surrogate models, automate pre/post-processing, and develop predictive solutions to solve Manufacturing Engineering and process challenges while ensuring data security and delivering measurable impact.
What You'll Do
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Collaborate with stakeholders to understand business challenges in the CFD space and solve them using API based customization and AI methodologies.
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Collect, clean, annotate, and prepare datasets for text analysis and image comparison tasks.
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Design, develop, and fine-tune AI/ML models for:
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Automating mesh generation, solver setup, and post-processing of CFD results
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Building optimization pipelines for thermal and fluid systems using AI-assisted approaches
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Evaluate, validate, and benchmark model performance using appropriate metrics.
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Deploy AI models into production environments in collaboration with IT/AI teams.
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Establish monitoring and maintenance processes to ensure model accuracy over time.
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Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements.
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Document workflows, results, and lessons learned for organizational knowledge sharing.
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Stay updated on advancements in neural networks, multi-physics simulations, surrogate modelling and physics-informed learning techniques.
Your Skills & Abilities (Required Qualifications)
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Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar.
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5+ years experience in CFD at Automotive Product Development / Manufacturing Engineering.
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2+ years experience in implementing AI solutions in CFD
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Should have executed at least 5+ years of Core CFD domain (from problem definition to deployment) experience.
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Strong programming skills in Python and C++ for automation and solver integration.
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Experience with ML frameworks like Pytorch, TensorFlow.
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Knowledge of surrogate modeling, reduced-order modeling (ROMs), and regression techniques.
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Experience in data handling (large-scale CFD datasets) and feature engineering(feature extraction from flow fields like velocity, pressure, turbulence quantities).
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Strong problem-solving and analytical mindset.
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Understanding of data annotation tools and MLOps workflows.
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Experience in domain-specific AI use cases (manufacturing, automotive, etc.).
