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 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 Masters degree or equivalent experience
- 5 years of experience leading sophisticated cross-functional technical projects from inception to completion
- A proven ability to create implement and refine durable large-scale processes
- Exceptional communication and interpersonal skills with a talent for building consensus
- A strong generalist mindset with the ability to deconstruct complex problems and drive toward clear optimized solutions
- Foundational understanding of machine learning concepts and the development lifecycle
- Expertise in leading infrastructure strategy for scalable high-performance ML systems (storage compute networking and benchmarking)
- Demonstrated success in a resource management role within a technical or engineering organization
- Deep practical knowledge of the modern ML development landscape and its associated challenges
- Programming and technical skills that enable hands-on contributions to tooling and ML systems
Required Experience:
Manager
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 f...
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 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 Masters degree or equivalent experience
- 5 years of experience leading sophisticated cross-functional technical projects from inception to completion
- A proven ability to create implement and refine durable large-scale processes
- Exceptional communication and interpersonal skills with a talent for building consensus
- A strong generalist mindset with the ability to deconstruct complex problems and drive toward clear optimized solutions
- Foundational understanding of machine learning concepts and the development lifecycle
- Expertise in leading infrastructure strategy for scalable high-performance ML systems (storage compute networking and benchmarking)
- Demonstrated success in a resource management role within a technical or engineering organization
- Deep practical knowledge of the modern ML development landscape and its associated challenges
- Programming and technical skills that enable hands-on contributions to tooling and ML systems
Required Experience:
Manager
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