Responsibilities include:* Performing model conversion from PyTorch , among other libraries, to the Core ML model format * Running and benchmarking models. Understanding the effect of computational graph representation on the model execution performance on neural engine, GPU, CPU. * Proficient in setting up and running open source ML models (e.g. Hugging Face), understanding ML pipelines and reasoning on which parts should be part of the model, and which outside the model as pre-processing and post processing steps * Adding graph passes for improving performance. Publishing examples of models that are converted in "performant" ways (example: the Apple Stable diffusion open source library)* Collaborate effectively with developers (internal and external). Be an active member of the open source CoreMLTools community on Github, interacting with developers, addressing GitHub issues etc* Implementing new operations / layers for neural networks * Improving model optimization documentation, writing examples, tutorials and guides