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Home›Jobs›Apple›ML Software Engineer, London
Apple

About Apple

The personal technology company redefining user experience

🏢 Tech, Hardware👥 1001+ employees📅 Founded 1976📍 Cupertino, CA⭐ 4.2
B2CB2BHardwareSaaSTelecommunicationseCommerce

Key Highlights

  • Market cap of $3 trillion as of 2022
  • Over 1 billion active devices worldwide
  • Comprehensive medical plans including mental healthcare
  • Paid parental leave and gradual return-to-work program

Apple Inc. (NASDAQ: AAPL), headquartered in Cupertino, CA, is the world's most valuable company with a market capitalization of $3 trillion as of 2022. Known for its iconic products such as the iPhone, iPad, and Mac, Apple serves over 1 billion active devices globally. The company has a strong commi...

🎁 Benefits

Apple offers comprehensive medical plans covering physical and mental healthcare, paid parental leave, and a gradual return-to-work program. Employees...

🌟 Culture

Apple's culture emphasizes an obsessive focus on user experience and consumer privacy, setting it apart from competitors. The company promotes inclusi...

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Apple

ML Software Engineer, London

Apple • London, England, United Kingdom

Posted 2 months ago🏛️ On-SiteMid-LevelMachine learning engineer📍 London
Apply Now →

Job Description

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.

Description

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.

Minimum Qualifications

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

Preferred Qualifications

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

Responsibilities

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

Eeo Content

At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. 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. Learn more

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