Design Optimization Engineer – Jet & Cryogenic Engines

Scope of Work

We are seeking a Design Optimization Engineer with strong fundamentals in multidisciplinary optimization, applied mathematics, and aerospace engineering. The role focuses on optimizing key performance and structural metrics of critical components in next-generation fighter jet engines and cryogenic rocket propulsion systems. You'll collaborate with aerodynamicists, structural analysts, and control systems teams to refine designs through iterative simulation and real-time digital twin feedback.

Nature of Work

• Design-space exploration and parametric modeling of engine components
• Application of topology, shape, and size optimization algorithms (e.g., genetic algorithms, adjoint methods)
• Development of high-fidelity simulation workflows for optimization cycles
• Use of digital twins and reduced-order models for real-time optimization feedback
• Integration of optimization pipelines with CAD/CAE tools
• Trade-off studies on performance vs manufacturability and reliability
• Collaboration with materials, CFD, structural, and controls teams

Job Requirements

• B.E./B.Tech or M.E./M.Tech in Aerospace, Mechanical, Applied Mathematics, or Computational Engineering
• Proficiency in optimization tools such as modeFRONTIER, HEEDS, Dakota, or in-house frameworks
• Working knowledge of MATLAB, Python (SciPy, NumPy, OpenMDAO, PyOpt), or similar
• Experience with FEA/CFD software: ANSYS, Abaqus, COMSOL, OpenFOAM
• Familiarity with sensitivity analysis, uncertainty quantification, and surrogate modeling
• Understanding of design constraints in turbomachinery and cryogenic environments
• Strong mathematical modeling, problem-solving, and documentation skills

Eligibility

• Indian nationals or those authorized to work in India
• Individuals with research, thesis, or published work in aerospace optimization are encouraged to apply
• Open to fresh graduates with outstanding academic or project records