Sr. AI, ML Research Engineer-2
SourceoBengaluruRemoteDirect career pageEst. 30–55 LPA
Posted on 16 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and apply advanced AI/ML methods specifically for computational fluid dynamics (CFD) and multi-physics simulation problems in fluid flow, heat transfer, turbulence, and thermal management.
- Create and deploy physics-informed neural networks, surrogate models, and reduced-order models to accelerate simulations while maintaining engineering accuracy.
- Collaborate with research, product teams, and external vendors to translate scientific ML research into production-ready tools and scalable engineering workflows.
Minimum Requirements
- PhD or MTech in Mechanical Engineering, Aerospace Engineering, Applied Mathematics, Computer Science, Physics, or related fields with strong emphasis on CFD or computational science.
- Strong foundation in computational fluid dynamics, numerical methods for PDEs, turbulence modeling, and heat transfer.
- Demonstrated experience with physics-informed neural networks or related scientific ML methods applied to engineering/scientific problems.
- Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
Ideal Candidate Profile
- Experienced in building end-to-end ML workflows including data preparation, training, evaluation, and deployment in HPC/Linux environments with GPU-based training.
- Skilled at integrating AI/ML models with CFD solvers, design optimization, digital twin platforms, and simulation automation workflows.
- Capable of driving technical strategy in physics AI, scientific machine learning, model validation, and complex engineering optimization based on strong interdisciplinary knowledge.