Our team focuses on building the best possible ecosystem for ML R&D engineers to build Apple-quality ML-based technologies. We develop numerous tools to facilitate development of ML models and collaboration around these ML models, and we manage the use of multiple resources such as training compute for Software Engineering, or disk footprint of on-device ML models throughout our operating systems. This unique blend of tooling and resource management offers a powerful opportunity to enhance the tools that support our policy initiatives. These initiatives span organizational boundaries and influence nearly every engineering team across the company.
In this role: you will focus on the resource management role of our team. You will be tasked to contribute to improvements on how we manage these resources from a technical and policy standpoint, and how we influence the rest of the company on these aspects. It is a highly cross-functional role with significant exposure to challenges across all aspects of the stack.
Bachelors or Master’s degree in Computer Science, Engineering, or equivalent experience
Skilled in leading infrastructure strategy to support scalable, high-performance ML systems across storage, compute, networking, and benchmarking.
Proficient in Python and/or C++
Validated experience in engineering resource management with strong communication and interpersonal skills
Experience in software automation
Understanding of fundamental machine learning concepts
Proven organizational skills in order to establish durable processes
Experience in web development
Deep curiosity in what ML workloads and ML models do, in order to be able to assess them and the associated resource requirements