Embedded AI/ML Engineers play a pivotal role in advancing Code Fusion Studio, an integrated development environment on embedded platforms.
Key Responsibilities:
* Collaborate with machine learning researchers to integrate novel ML algorithms and data processing pipelines into Code Fusion Studio, enabling seamless edge AI development.
* Design and implement robust software tools, plug-ins, and compilers within the IDE to streamline AI model deployment and performance optimization across ADI's embedded platforms.
* Play a central role in shaping the strategy and architecture for quality assurance, developer experience, and long-term maintainability of embedded AI toolchains.
Requirements:
* Experience developing software tools and frameworks for embedded AI workflows.
* Background in machine learning algorithms (CNN, DNN) and experience deploying them on embedded systems.
* Familiarity with model optimization techniques (quantization, pruning, compilation) and deployment pipelines for embedded AI.
* Familiarity with neural network accelerators and strategies for efficient neural network execution on such hardware.
* Strong background in embedded software and computer architecture.
* Excellent problem-solving and troubleshooting skills.
* Proficient in C/C++ programming.
* Python is essential; JavaScript experience is a plus.