Develops research methods for context discovery, retrieval, multimodal representation, reasoning, tool calling, metadata management, and trustworthy AI data pipelines. Builds and evaluates foundation models across language, vision, time series, and scientific applications. The role combines applied research with hands-on engineering, including MLOps, agentic AI, knowledge-infused learning, pipeline optimization, and collaboration with software teams and external partners.

The role involves developing software tools for semiconductor compilers, creating an ecosystem for efficient IP generation, and requires knowledge in circuit design and programming.

The Physical Design Engineer will lead efforts in solving physical design challenges, improve RTL-to-GDS methodologies, and integrate AI/ML solutions into CAD flows, focusing on performance and runtime improvements.