On-device ML Engineering Manager (Tools & Services

DESCRIPTION

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. This role focuses on giving ML developers fast, accurate, and actionable insight into how their models execute on Apple devices. We're 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 ML.

As 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. The 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.

• BS/MS/PhD in Computer Science or Electrical Engineering. Two or more years of strong and validated management experience. Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch).
• Experience delivering web services and/or developer-facing tools, spanning frontend and backend.
• Excellent communication skills.
• Track record of creating clean software architectures, intuitive designs, and high-performance extensible software.
• Solid 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 Execu Torch).
• Experience with performance profiling, benchmarking, and analysis tooling.
• Experience building and operating infrastructure for running workloads across fleets of devices.
• Experience associating low-level performance data with framework-level operations.
• Experience with MLIR / LLVM compiler technologies.