About the job
Imagine being at the forefront of an evolution where cutting-edge AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.
Responsibilities
Ensure functional and performant integration of Apple’s ML models across the inference stack.
Integrate Apple’s ML tools into internal and external model repositories to demonstrate and stress-test model ingestion with peak efficiency and performance.
Develop optimizations across the pipeline, including model-level transformations, custom operations, or compiler optimizations to improve inference efficiency.
Spearhead the integration of the cutting-edge ML models with peak performance, using these examples to validate or improve Apple’s inference stack.
Qualifications
Minimum
Bachelors in Computer Sciences, Engineering, or related discipline.
Proficient in Python programming. Some familiarity with C++ is required.
Proficiency in at least one ML authoring framework, such as PyTorch, MLX, and JAX.
Understanding of ML fundamentals, including common architectures such as Transformers.
Understanding of GPU programming paradigms.
Strong communication skills, including ability to communicate with cross-functional audiences.
Preferred
Experience with C++, Swift.
Experience with GPU kernel optimizations.
Experience with MLIR/LLVM or similar compiler toolchains.
Familiarity with Hugging Face or other model repositories.