Ai Hardware Design Engineer

We are seeking an AI Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. In this role, you will design, develop, and optimize generative AI models and workflows for applications such as content creation, product design, and intelligent automation.

Key Responsibilities:

• 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 to infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins by combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments for efficient model deployment.
• Develop multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.

Required Skills & Qualifications:

• Education: Masters or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or a 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.
  • Proven experience (code repositories, publications) bridging simulation software, hardware design, and ML.

Experience Required: 68 years

Skills:

• Python
• Machine Learning