Machine Learning Architect, Platform Architecture

What you'll do

• Create optimized implementations of ML workloads on Apple silicon including Neural Engine, GPU, and CPU.
• Develop performance models and simulations of future hardware in collaboration with IP and SoC architecture teams.
• Create high-level performance models of emerging ML techniques to analyze system architecture trade-offs.
• Evaluate ML model optimization techniques from literature through experimentation and analysis.
• Propose new architectural ideas based on research to inform hardware and algorithm direction.
• Provide guidance to software and algorithm teams on making workloads run efficiently on SoCs.
• Prototype algorithms on CPU/GPU/Neural Engine and analyze performance metrics.

What we're looking for

• Experience in C/C++ and/or Python.
• Experience in hardware IPs such as ML accelerators, GPU/CPU, or image/video processors.
• Experience with ML frameworks like PyTorch and efficient implementations of machine learning algorithms.
• MS or PhD in EE/CE/CS or related field (preferred).
• 20+ years of relevant experience (preferred).
• Experience optimizing and deploying ML models or runtime frameworks in production inference/training environments (preferred).
• Experience designing experiments to evaluate ML model optimization techniques (preferred).
• Bachelor’s degree.