As an engineer in this role, you will be primarily focused on developing APIs in coremltools to enable ML engineers to efficiently author/convert ML models to CoreML, including any feedback APIs to help them evaluate the CoreML programs. The conversion APIs also include optimizations to enable peak performance on Apple devices, such as quantization, compression, distillation, etc. The role requires a good understanding of ML modeling (architectures, training vs inference trade-offs, etc.), and a good understanding of designing Python APIs and packages. Key responsibilities:Develop APIs in coremltools for ML engineers to efficiently convert models from ML frontends (such as PyTorch, JAX) into CoreML’s model representation.Develop APIs, and tools for ML engineers to evaluate and converted/authored programs.