What are the responsibilities and job description for the ML Software Engineer position at Apple, Inc.?
People at Apple don't just build products - they craft the kind of experience that has revolutionized entire industries. The diverse collection of our people and their ideas inspire innovation in everything we do. Our team builds ML-inference applications and services on Apple Silicon in the datacenter, specifically focusing in recent years on generative AI as part of the Private Cloud Compute component of Apple Intelligence. Imagine what you could do here! Join us. Be you.
Description
As part of the team you will help engineer continuous improvements in stability and performance for private cloud compute, as well as help implement entirely new functionality as it emerges from the research community, in collaboration with product teams throughout Apple. We write performant and scalable frameworks (in Swift and C ) to distribute and coordinate ML inference tasks to different hardware acceleration IP blocks on different SoCs.
We're a collection of highly skilled and friendly engineers who value each other's opinions and experience. We strive for excellence and believe strongly in the quality of our output. We have formed a team of domain experts who specializes in specific core subject areas, and also have broad experience of cloud software services and platforms. You will integrate inference code into a full service stack to ensure that user traffic is served reliably and performantly, and will have a strong focus on developing code that is easy and safe to develop, update and monitor.
Minimum Qualifications
Experience working as a software engineer on large production systems.
Experience programming in: Swift, C, C , iOS/macOS or Xcode.
Practical experience running machine learning models and evaluating them for quality and performance metrics.
Preferred Qualifications
Familiar with Apple ML stack (ANE, CoreML, MPS/Metal).
High-level general distributed ML stack (PyTorch-distributed, NCCL) and high throughput inter-chip communication systems.
On-device iOS development.
Description
As part of the team you will help engineer continuous improvements in stability and performance for private cloud compute, as well as help implement entirely new functionality as it emerges from the research community, in collaboration with product teams throughout Apple. We write performant and scalable frameworks (in Swift and C ) to distribute and coordinate ML inference tasks to different hardware acceleration IP blocks on different SoCs.
We're a collection of highly skilled and friendly engineers who value each other's opinions and experience. We strive for excellence and believe strongly in the quality of our output. We have formed a team of domain experts who specializes in specific core subject areas, and also have broad experience of cloud software services and platforms. You will integrate inference code into a full service stack to ensure that user traffic is served reliably and performantly, and will have a strong focus on developing code that is easy and safe to develop, update and monitor.
Minimum Qualifications
Experience working as a software engineer on large production systems.
Experience programming in: Swift, C, C , iOS/macOS or Xcode.
Practical experience running machine learning models and evaluating them for quality and performance metrics.
Preferred Qualifications
Familiar with Apple ML stack (ANE, CoreML, MPS/Metal).
High-level general distributed ML stack (PyTorch-distributed, NCCL) and high throughput inter-chip communication systems.
On-device iOS development.