Senior ML Ecosystem Engineer

Apple Inc.

Greater London

On-site

GBP 70,000 - 110,000

Full time

14 days+

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Job summary

GGML's Metal Pro Apps and ML 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.

You will analyze developers' products and report on their use of the ML API, recommending optimizations, contribute platform enablement and improvements to key open source projects, and host developers during in-person engineering sessions, becoming a key

Qualifications

  • Experience with GPU compute frameworks and optimization.
  • Strong programming & problem-solving abilities.
  • Solid understanding of machine learning fundamentals.
  • Excellent written and verbal communication skills.

Responsibilities

  • Analyze developers' products and report ML API usage, recommending optimizations.
  • Contribute platform enablement and optimisations to key open source projects.
  • Host developers during in-person engineering sessions.
  • Support ML app development with documentation, training, and relationship building.

Skills

GPU compute framework development
Proven programming & problem-solving
Machine learning fundamentals
Written & verbal communication

Job description

Selection changes the language of the page/content

London, England, United Kingdom Software and Services

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 TVApple’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

GGML's Metal Pro Apps and ML 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. Contribute platform enablement and optimisations to key open source projects. 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 and key middleware.
  • 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 and open source communities, managing the relationships, and driving the engineering work
Minimum Qualifications
  • GPU compute framework development, maintenance, and optimization.
  • Proven programming and problem-solving skills.
  • Good understanding of machine learning fundamentals.
  • Exemplary written and oral communication skills.
Preferred Qualifications
  • GPU compute programming models & optimization techniques.
  • Machine learning development using one or more ML frameworks (PyTorch, TensorFlow. or JAX).
  • Experience with system level programming and computer architecture.

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As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations.

Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law.

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