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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 thebusiness.
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 Youll Do
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.
Your Skills & Abilities (Required Qualifications)
Bachelors or Masters DegreeMechanical/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.).
What Will Give You A Competitive Edge (Preferred Qualifications)
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.
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Required Experience:
Senior IC
Full-Time