Embedded AI Tools Engineer

Role Overview

The Embedded AI Tools Engineer will design and implement embedded AI deployment infrastructure, model optimization tools, and hardware-aware workflows for heterogeneous intelligent-edge SoCs at Analog Devices. You will bridge the physical and digital worlds through analog, digital, AI, and software technologies.

Key Responsibilities:

• Design, test, implement, and release novel AI model deployment tools for heterogeneous computer architectures (DSPs, NPUs, CPUs) within SoCs.
• Build end-to-end workflows spanning model development through production on resource-constrained devices.
• Develop infrastructure for hardware-aware model design, including architecture mapping techniques that adapt neural network structures to specific hardware capabilities.
• Create and optimize compilation pipelines enabling quantization, pruning, layer fusion, and code generation for embedded platforms.
• Prototype agentic AI workflows leveraging autonomous agents for automated co-optimization and intelligent architecture search.