ML Software Engineer, London
You'll work with Swift and C++ to build ML-inference applications and services on Apple Silicon, focusing on generative AI within Apple Intelligence's Private Cloud Compute. The team engineers frameworks to distribute and coordinate ML inference tasks across hardware acceleration blocks, integrating inference code into production service stacks while ensuring reliability and performance. You'll collaborate across Apple to implement new functionality from research, improve system stability, and maintain code quality in large-scale cloud systems.
Free Tailor for ATS: 10/10 runs left
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.
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.
Quality focus - produce reliable, maintainable, deliverable software
Comfortable diving deep - working across multiple levels of abstraction
Good at handling relationships & communication - collaborate well with colleagues across a wide range of functions
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
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