On-device ML Engineering Manager (Tools & Services)

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 Apples hardware and software team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices optimization toolkits to optimize these models to better suit the target devices machine learning compilers and runtimes to execute these models as efficiently as possible and the benchmarking analysis and debugging toolchain needed to improve on new model iterations. nnThis infrastructure underpins most of Apples critical machine learning workflows across Camera Siri Health Vision etc. and as such is an integral part of Apple group is seeking an Engineering Manager to lead the Performance Tools and Services team with a focus on the tools services and infrastructure that make on-device ML performance measurable understandable and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution the backend web services that power them and the on-device toolchain that gathers low-level performance data associates it with high-level (PyTorch) framework-level ops and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.

We are building the first end-to-end developer experience for ML development that by taking advantage of Apples vertical integration allows developers to iterate on model authoring optimization transformation execution debugging profiling and analysis. nnThis role focuses on giving ML developers fast accurate and actionable insight into how their models execute on Apple devices. Were looking for a manager that has proven experience in and passion for providing high quality developer tools and capabilities in the fast paced and dynamic space of the manager in this role you will lead a diverse team spanning full-stack web development backend services distributed systems and low-level on-device performance tooling. You will partner with leaders across the organization and company to develop our platform while supporting clients internally and externally. nnThe role requires a solid technical understanding of ML execution on device performance analysis and profiling and the systems that connect low-level signals to framework-level (e.g. PyTorch) semantics.

Leading and growing the team that builds the frontend web services for introspecting ML models and their on-device execution the backend services that support them and the on-device toolchain for gathering and reporting low-level performance future efforts to improve the model authoring performance profiling improve model repeat workflow making it faster and more insightful for ML the infrastructure for running ML inference across fleets of devices ensuring it is reliable scalable and produces trustworthy performance hiring and guiding the career of talented ML software and tools with cross functional partners to push the state-of-the-art of on-device ML functionality and performance.

BS/MS/PhD in Computer Science or Electrical or more years of strong and validated management of ML development and workflows including at least one authoring framework experience (e.g. PyTorch).nExperience delivering web services and/or developer-facing tools spanning frontend and communication record of creating clean software architectures intuitive designs and high-performance extensible programming skills in at least one of the following languages: Python Swift Objective-C C/C.

Experience with on-device ML frameworks (Core ML Win ML ONNX TF Lite or ExecuTorch).nExperience with performance profiling benchmarking and analysis building and operating infrastructure for running workloads across fleets of associating low-level performance data with framework-level with MLIR / LLVM compiler technologies.