Pro Apps ML Ecosystem Engineer

at  Apple

SUMMARY

Posted: 16 Oct 2024
Weekly Hours: 35
Role Number:200573554
Apple’s Metal Pro Apps Ecosystem team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV Apple’s GPU, Graphics and Displays org provides the graphics software foundation across all of Apple’s innovative products, including Mac, iPad, iPhone, and Apple TV. Our responsibilities encompass the frameworks, developer tools, and device drivers for the GPU and Display on Apple’s hardware. MPSGraph provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple to improve the ML inference potential and performance applications on for iOS, macOS and Apple TV.

DESCRIPTION

GGD SW’s Metal Pro Apps Ecosystem team is now seeking a world-class, driven, and dedicated engineer to work alongside developers to integrate and optimize ML workloads for Apple’s ANE and GPU silicon into their macOS and iOS applications. Are you ready to engage with developers to advance their success using Apple’s tools and technologies related to ML? Responsibilities: Analyze developers products and report on their use of the ML API, recommending optimizations, algorithms, and techniques to improve their applications. Host developers during in-person engineering sessions. You will be a key source for all aspects of ML application development, including engineering, documentation, training, and relationship management. Responsibilities: * Support adoption of GPU-accelerated training by 3rd party Apps. * Performing in-depth analysis of an application’s full stack to drive the best possible performance across hardware families. * Representing Apple to these 3rd party clients, managing the relationships, and driving the engineering work

• Proven programming and problem-solving skills.
• Good understanding of machine learning fundamentals.
• GPU compute programming models & optimization techniques.
• GPU compute framework development, maintenance, and optimization.

• Machine learning development using one or more ML frameworks (TensorFlow, PyTorch or JAX).Experience with system level programming and computer architecture.

PREFERRED QUALIFICATIONS

• You must be enrolled as a student on a Masters, PhD or equivalent course

• Proven programming and problem-solving skills.
• Good understanding of machine learning fundamentals.
• GPU compute programming models & optimization techniques.
• GPU compute framework development, maintenance, and optimization.
• Machine learning development using one or more ML frameworks (TensorFlow, PyTorch or JAX).Experience with system level programming and computer architecture