The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products.
The On-device ML Performance team has the responsibility to analyze latency, memory, power and numerical correctness of the latest machine learning models running on Apple SoC’s, and to make Apple’s ML software stack take full advantage of the capabilities in Apple’s ML accelerators. The work from this cross functional team enables model developers’ decisions to optimize performance via advanced techniques such as quantization, sparsity, performance and accuracy tradeoffs. The work of this team impacts all new Apple HW and ML Inference on them.
Our group is looking for an On-device ML Performance Engineer, with technical expertise in computer architecture, performance, memory, power, ML model architectures and on-device ML inference. The role entails deep analysis of ML inference from the SW stack and low level drivers to HW debug involving CPU, GPU, Apple Neural Engine, system memory and power.
