Role OverviewWe are seeking a highly experienced Consulting R&D Engineer specializing in solver-based simulation and AI-driven surrogate modeling across CFD, FEA, and Multiphysics domains. The consultant will support R&D teams, product engineering groups, and innovation programs by delivering advanced simulations, developing customized
computational workflows, and enabling accelerated virtual prototyping through AI/ML-based modeling.This role is ideal for an expert who thrives in flexible, project-driven environments and can contribute both technically and strategically.Key Responsibilities
- Provide specialized consulting services in CFD, FEA, and Multiphysics simulations across diverse industrial applications.
- Execute solver-based analyses including fluid flow, heat transfer, structural, multiphase, nonlinear, and coupled physics problems.
- Develop and deploy AI/ML surrogate models , reduced-order models (ROM), and digital twin components to accelerate simulation cycles.
- Design efficient simulation workflows , including meshing, boundary condition setup, solver selection, and convergence strategies.
- Build custom scripts and workflow automation using Python, MATLAB, or C++ , integrating simulation and AI pipelines.
- Interpret complex simulation data, generate actionable insights, and recommend design improvements to client teams.
- Engage with R&D, design, and product engineering stakeholders to understand requirements and propose optimized simulation strategies.
- Support HPC execution of large-scale simulations and guide clients on cluster utilization and solver performance optimization.
- Validate models using experimental or historical data and calibrate surrogate models for accuracy and robustness.
- Deliver technical reports, presentations, and advisory input to client leadership and engineering teams.
- Provide training, mentoring, or capability-building sessions for client teams on simulation methods, tools, and AI/ML applications.
Required Qualifications
- Bachelor’s degree in Mechanical, Aerospace, Chemical, Materials, Civil Engineering, or related fields.
- Strong background in fluid mechanics, structural mechanics, heat transfer, and numerical methods .
- Expertise in major CFD tools:
- ANSYS Fluent, CFX, STAR-CCM+, OpenFOAM, COMSOL
- Expertise in major FEA tools:
- ANSYS Mechanical, Abaqus, LS-DYNA, NASTRAN, COMSOL
- Proven experience executing complex simulations independently with minimal guidance.
- Strong programming experience in Python (required) , with exposure to C++/MATLAB for algorithm development.
- Knowledge of discretization schemes, turbulence models, nonlinear FEM, multiphase physics, and solver stability.
Preferred Qualifications (Consulting-Oriented)
- Master’s degree or PhD in Computational Mechanics, CFD, Applied Mathematics, or related advanced fields.
- Experience building and deploying ML/AI models for:
- Surrogate modeling
- ROM model development
- Data-driven prediction (e.g., neural networks, Gaussian processes
- Experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn.
- Hands-on experience integrating AI models with traditional solvers to create hybrid simulation workflows.
- Experience with HPC clusters, parallel solvers (MPI/OpenMP), and job schedulers.
- UDFs, custom solver extensions, or code-level customization in OpenFOAM/Fluent/Abaqus
Consulting Competencies
- Strong ability to diagnose client needs and propose the right simulation or AI-based solutions.
- Capable of managing multiple projects and delivering high-quality results within deadlines.
- Excellent communication skills, including client-facing discussions and technical presentations.
- Ability to translate complex simulation outcomes into clear, actionable engineering guidance.
- Independent, proactive, and innovation-focused mindset.
Industry Experience
- Manufacturing
- Automotive & EV
- Electronics & Semiconductor
- Aerospace & Defense
- Energy, Renewables, Thermal Systems
- Chemical Process, Oil & Gas
- Biomedical Engineering
- Consumer Products & Industrial Engineering
Engagement Model
- Contract / Consulting / Project-based
- Remote, onsite, or hybrid support depending on client needs
- Engagement may include short-term simulation tasks, long-term R&D support, or multi-disciplinary innovation projects.
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