AIML - Machine Learning Engineer, On-Device Machine Learning
Job Description
Summary
Help us bring state-of-the-art ML models to the entire Apple ecosystem, enabling the next generation of ML-based experiences in a privacy-preserving way! Our team is responsible for the core framework that launches neural-network workloads on Apple devices. We build the bridge between the compute resources available on Apple hardware and an entire universe of ML models, trained by feature teams throughout Apple and by our developer community. Your work on our team will enable increasingly sophisticated models throughout our products, from the computer vision models that process every camera frame in the Apple Vision Pro, to the language models that allow human-computer interaction to feel more human. By developing the underlying representation, pipeline, and runtime executor for these workloads, including the mechanisms for mapping them to the CPU, GPU, and Neural Engine, you will play a critical role in expanding what is possible for Apple and for the world.
Description
* Design and implement improvements to Apple’s Model Intermediate Language (MIL), the intermediate representation of neural-network workloads shared across the inference stack
* Develop the mechanisms for analyzing and transforming MIL workloads
* Build the tightly integrated pipeline that optimizes and compiles models and then orchestrates their execution on device
* Optimize our software stack for extensibility and experimentation, paving the way for ongoing innovation
* Collaborate with CPU, GPU, and Neural Engine hardware backends to push inference performance and efficiency
* Work closely with feature teams to facilitate and debug the integration of increasingly sophisticated, state-of-the-art models
* Develop the mechanisms for analyzing and transforming MIL workloads
* Build the tightly integrated pipeline that optimizes and compiles models and then orchestrates their execution on device
* Optimize our software stack for extensibility and experimentation, paving the way for ongoing innovation
* Collaborate with CPU, GPU, and Neural Engine hardware backends to push inference performance and efficiency
* Work closely with feature teams to facilitate and debug the integration of increasingly sophisticated, state-of-the-art models
Minimum Qualifications
- Excellent C/C++ programming and debugging skills
- Enthusiasm for API design and software architecture
- Experience with CMake, Xcode or other equivalent build system
- Expertise with performance optimization
- Exceptional verbal and written communication skills
- BS/MS Computer Science or Electrical Engineering with Solid industry experience (5+ years)
Preferred Qualifications
- PhD in Computer Science or Electrical Engineering
- Familiarity with Machine Learning Compiler Technologies such as LLVM/MLIR
- Experience with modern neural-network architectures and deep learning libraries
