GenDesign / Inverse Design Ai Engineer

• We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.
• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.

Required Skills & Qualifications

Education: Master s or Ph.D. in Materials Science, Computational Engineering, AI/ML, or related field.

Technical Expertise:

• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with generative AI (LLMs, diffusion models, graph-based models).
• Knowledge of computational materials methods (DFT, MD, phase-field modeling).

Additional Skills:

• Familiarity with MLOps, HPC environments, and cloud deployment.
• Understanding of thermodynamics, crystallography, and mechanical properties of materials.