Imagine what you could do here. At Apple, new ideas have a way of becoming great products very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
The Apps Engineering team, empowering millions of writers, musicians, filmmakers, photographers, designers and creators worldwide, is seeking a software engineer to work on Large Language Model interfaces, fine-tuning and deployment. You’ll work on cutting-edge AI applications, helping deploy LLM workflows across diverse environments while maintaining Apple’s high standards for quality, performance, and creative ethics.
Description
Make a difference. As a Software Engineer specializing in LLM Workflows on the Apps Engineering team, you'll collaborate daily with machine learning researchers, application engineers, framework engineers, and product designers to work on advanced language models and task automation.
Your work will span the entire development lifecycle, from defining data requirements and evaluation frameworks to deploying LLM workflows across tools and applications. This role requires expertise in prompt engineering, retrieval-augmented generation, and model fine-tuning to create intelligent, context-aware experiences.
Minimum Qualifications
Experience fine-tuning Large Language Models for specific domains or tasks, alongside integrating LLMs and deploying fine-tuned adapters.
Experience developing software applications using Python, Swift, or C++.
Experience with REST APIs, JSON, and working with LLM services (e.g., OpenAI APIs).
Experience building data collection and evaluation pipelines for machine learning systems.
Preferred Qualifications
BS/MS in Computer Science, Machine Learning, or related technical field, or 3 years of equivalent work experience.
Experience with prompt engineering and optimization techniques for LLMs.
Experience implementing retrieval-augmented generation (RAG) systems.
Experience developing agentic workflows and orchestration systems.
Experience with local model deployment and on-device LLM inference.
Experience with Apple's Foundation Model framework or similar ML frameworks.
Experience collaborating with framework engineers to optimize ML infrastructure.
Experience working with creators, audio/video production, or creative software applications.
Responsibilities
Design and implement LLM integration for applications and tools, deploying language models across diverse environments.
Develop prompt engineering strategies and RAG systems to enable context-aware AI capabilities.
Build evaluation frameworks and data collection pipelines to measure and improve LLM performance.
Work cross-functionally with ML researchers, app engineers, and framework teams across Apple to prototype and validate AI-driven features.
Implement fine-tuning workflows to adapt foundation models for specific domains and tasks.
Optimize LLM inference performance for deployment on macOS and iOS devices, ensuring responsive user experiences.
Contribute to the full feature development lifecycle from concept through launch, iterating based on evaluation metrics and user feedback.
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. We will work with applicants to make any reasonable accommodations.
