Responsibilities

• Lead the research and development of novel AI architectures that fuse vision data with temporal manufacturing process data to predict final product quality.
• Develop advanced methodologies for Root Cause Analysis (RCA), moving beyond correlation to establish causal links between process variables and inspection outcomes.
• Design and implement Knowledge Graphs and semantic reasoning layers that integrate domain expertise with LLMs/VLMs to automate final sentencing and provide explainable AI (XAI) insights.
• Architect and fine-tune state-of-the-art multimodal models to enable text-prompt able vision inspection and contextual decision-making.
• Pioneer the use of Temporal Transformers or Physics-Informed Neural Networks (PINNs) to analyze complex manufacturing time-series data for anomaly detection and yield prediction.
• Document research in high-impact internal reports or patent filings and stay at the forefront ...