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Senior Engineering Program Manager for Machine Learning Compute Infrastructure
2 months ago
We are seeking a highly skilled Senior Engineering Program Manager to join our Machine Learning Compute Infrastructure team at Apple. As a key member of our team, you will be responsible for establishing cross-functional partnerships with internal stakeholders to drive the development and deployment of our machine learning platforms.
Key Responsibilities- Collaborate with engineering teams to define a partnership strategy across the entire ML ecosystem, including 3rd party public cloud, Apple's internal cloud, silicon vendors, and OSS providers.
- Work with best-in-class engineering teams and developers to design efficient technologies that accelerate the ML lifecycle.
- Translate product requirements into technical use cases, helping to mitigate risks and ensure successful execution.
- Define new computing modalities using resources native to the cloud and take that vision to market in collaboration with internal and external partners.
- 5+ years of product and/or technical program management experience in distributed computing, large-scale cloud infrastructure, GPU/TPU usage for ML training, software and computing architectures, container stack, and networking.
- Experience working with large-scale GPU-based AI applications, such as natural language processing and recommendation, for training and inference or direct experience in building or managing cloud computing infrastructure and technologies.
- Proficiency in multitasking and leading sophisticated programs with cross-functional teams, with a track record of developing and bringing outstanding platforms to market.
- 5+ years of work experience in product/program and/or solutions architecture or developer roles.
- MS/PhD in EE, CS, Math, or Physics or equivalent work experience.
- Strong desire to learn, skills for problem-solving, and the ability to make sophisticated trade-offs.
- Experience driving technical partnerships with internal and external cloud, software partners.
- Knowledge of computer systems and cloud infrastructure architecture.
- Familiarity with AI frameworks (e.g. TensorFlow, PyTorch, or MxNet) and/or GPU development experience.
