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Senior Engineer / Lead Engineer - Virtual Engineering - AI CFD

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General Motors

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Location:
India , Bengaluru

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

Not provided
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Job Description:

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.

Job Responsibility:

  • Collaborate with stakeholders to understand business challenges in the CFD space and solve them using API based customization and AI methodologies
  • Collect, clean, annotate, and prepare datasets for text analysis and image comparison tasks
  • Design, develop, and fine-tune AI/ML models for: Automating mesh generation, solver setup, and post-processing of CFD results
  • Building optimization pipelines for thermal and fluid systems using AI-assisted approaches
  • Evaluate, validate, and benchmark model performance using appropriate metrics
  • Deploy AI models into production environments in collaboration with IT/AI teams
  • Establish monitoring and maintenance processes to ensure model accuracy over time
  • Ensure that all AI solutions comply with organizational data security, confidentiality, and regulatory requirements
  • Document workflows, results, and lessons learned for organizational knowledge sharing
  • Stay updated on advancements in neural networks, multi-physics simulations, surrogate modelling and physics-informed learning techniques

Requirements:

  • Bachelor’s or Masters Degree Mechanical/Automobile/Production /Mechatronics Engineering discipline or similar
  • 5+ years experience in CFD at Automotive Product Development / Manufacturing Engineering
  • 2+ years experience in implementing AI solutions in CFD
  • Should have executed at least 5+ years of Core CFD domain (from problem definition to deployment) experience
  • Strong programming skills in Python and C++ for automation and solver integration
  • Experience with ML frameworks like Pytorch, TensorFlow
  • Knowledge of surrogate modeling, reduced-order modeling (ROMs), and regression techniques
  • Experience in data handling (large-scale CFD datasets) and feature engineering(feature extraction from flow fields like velocity, pressure, turbulence quantities)
  • Strong problem-solving and analytical mindset
  • Understanding of data annotation tools and MLOps workflows
  • Experience in domain-specific AI use cases (manufacturing, automotive, etc.)

Nice to have:

  • Exposure to Physics-Informed Neural Networks (PINNs) and Neural Operators for PDE-based learning
  • Familiarity with Bayesian optimization and DOE
  • Hands-on with cloud-based CFD simulation platforms
  • Exposure to ML Ops practices for model deployment and monitoring
  • Strong problem-solving mindset and curiosity for AI innovation
  • Ability to translate domain problems into AI solutions
  • Collaboration skills to work with cross-functional teams
  • Clear communication of technical concepts to non-technical stakeholders

Additional Information:

Job Posted:
March 03, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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