Job Description

Role Overview


We 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 ResponsibilitiesProvide

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.