SWE - Applied Machine Learning Engineer

at  Apple

London, England, United Kingdom -

Start DateExpiry DateSalaryPosted OnExperienceSkillsTelecommuteSponsor Visa
Immediate02 Dec, 2024Not Specified03 Sep, 2024N/AComputer Science,Ml,Xcode,Machine Learning,Multiple Disciplines,Foundation,Artificial Intelligence,Software,Developer Tools,CodeNoNo
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Description:

SUMMARY

Posted: 29 Aug 2024
Weekly Hours: 35
Role Number:200565377
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something - you’ll add something. Our Developer Documentation team seeks a creative, motivated, and passionate technical leader who has a robust knowledge of large language models (LLMs), generative AI, and proven experience with code generation. An ideal candidate has the ability to lead diverse cross-functional efforts to build the next generation of ML tools for software developers. Strong engineering fundamentals and a passion for code generation models are required.

DESCRIPTION

As an Applied ML Manager in the Developer Publications Intelligence team, you will lead a multi-discipline team of passionate engineers to design, fine-tune, and produce models that will be used by existing and future tools produced by Apple for third-party developers. We are looking for exceptional candidates to help define the future of Swift code generation in our tools and beyond. Your role is to ensure Apple and our third-party developers using Xcode deliver extraordinary software products to millions of customers around the world! Your duties will include: - Leading the exploration and application of Large Language Models (LLMs) for generating code in Apple’s developer tools - Translating the latest research into high-quality systems and models that can be practically applied to further improve Swift code generation - Actively engaging in all aspects of model development, from ideation, training, experimentation to deployment - Collaborating with data collection, model evaluation, and tool integration teams to develop and implement model solutions - Fine-tuning models and making them available for engineers to evaluate and define further experiments

  • Proficiency using open-source ML toolkits and frameworks (e.g., PyTorch, TensorFlow, OpenNMT)Strong programming skills (Python, C/C++, Swift, or other language)

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PREFERRED QUALIFICATIONS

  • BS, MS or PhD in Computer Science, Artificial Intelligence, or Machine Learning (or equivalent experience) Experience with Machine Learning (ML), with a particular focus on Large Language Models (LLM) that generate code
  • Proven ability to comprehend, interpret, and apply cutting-edge research into customer-oriented products, particularly developer tools
  • Comprehensive knowledge and hands-on experience with fine-tuning approaches, model recipes, and training models
  • Experience adapting re-trained LLMs for downstream tasks
  • Proven experience leading a team of ML/software engineers
  • Experience using Xcode to build software for Apple’s platforms
  • Proficiency with the Swift programming language
  • Proficiency with Apple’s development APIs (SwiftUI, Foundation, etc)
  • Comfortable working cross-functionally, bringing together multiple disciplines and expertise

Responsibilities:

  • Proficiency using open-source ML toolkits and frameworks (e.g., PyTorch, TensorFlow, OpenNMT)Strong programming skills (Python, C/C++, Swift, or other language


REQUIREMENT SUMMARY

Min:N/AMax:5.0 year(s)

Computer Software/Engineering

IT Software - Application Programming / Maintenance

Software Engineering

Phd

Proficient

1

London, United Kingdom