Description
As an engineer in this role, you will focused on developing, using APIs in Core ML tools that enable ML engineers to efficiently author/convert ML models to CoreML. You will ideate, design, and stress test the gamut of optimizations required to ingest these models, ranging from source level optimizations (e.g., in the PyTorch program), to custom optimizations after converting to CoreML’s model representation. We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple’s vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The coremltools authoring and conversion APIs are the entrypoint to the rest of the infrastructure stack. We are looking for someone who is highly self motivated and passionate about ML modeling (architectures, training vs inference trade-offs, etc.), ML deployment optimizations (e.g., quantization). If you have a proven track record of developing and working with the internals of an ML python library, writing high quality code and shipping software, we strongly encourage you to apply.