Summary
An overview of the key responsibilities for an AI/ML software engineer focused on optimizing performance for Arm-based architectures.
AI/ML Software Engineer Role Responsibilities
Highlights
Core Engineering Responsibilities
Collaborate with cross-functional teams to translate research into production-quality software. Focus on designing and optimizing machine learning models for Arm-based platforms, ensuring scalability across edge, embedded, and cloud environments.
Technical Development and Architecture
Develop high-performance AI components, including libraries and compilers using Python and C/C++. Contribute to system-level architecture design for next-generation processors and accelerators to support reliable AI workload execution.
Optimization and Workflow Integration
Implement AI/ML workflows using frameworks like TensorFlow, PyTorch, and ONNX. Perform deep analysis of the hardware-software stack to optimize model execution, memory usage, and power efficiency.