SWE – Applied Machine Learning Manager, Developer Publications Full-time

Summary
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