Customer Systems is part of IS&T and drives the technology behind Apple's customer support experience — from contact center operations to the software powering the iconic Genius Bar. The team also builds and operates AppleCare's online support platform, which handles 6 billion visits per year, delivering seamless, high-quality support to Apple customers around the globe.
At Apple, we are driven to deliver exceptional experiences through ultra-fast, thoughtfully designed, and meticulously crafted solutions. Our team is not just any group; we are a highly motivated, fast-paced, and dynamic collective of professionals committed to scaling new heights and achieving excellence. We seek individuals who strive beyond mediocrity and are relentless in their pursuit of perfection.
Contribute to model development and fine-tuning workflows for generative AI features.
Design and evaluate retrieval strategies for grounding large models in product-relevant data.
Prototype and benchmark multi-agent collaboration systems for structured reasoning tasks.
Partner with data and platform engineers to ensure scalable deployment and monitoring.
Description
Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS&T) organization. IS&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless.
Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.
The Customer Support AI team is responsible for building multi-turn, conversational, agentic applications and frameworks to support Apple customers across numerous lines of business. You’ll be contributing hands on to a team that consists of engineers, data scientists & researchers to enhance a multi-modal, multi-agent platform with a key focus on incorporating research to improve, latency, cost and customer experience. This is an incredible opportunity to contribute innovation & research to a well established generative AI platform within Apple. There is a huge amount of opportunity and growth within this space!
Minimum Qualifications
5+ years of hands-on experience in ML, backend engineering, data engineering 1-2 years of hands-on experience in training, fine-tuning, or evaluating LLMs Foundational understanding of RAG architectures and vector-based retrieval systems Strong experience partnering with business and engineering team to deliver AI solutions Bachelor's or Master's degree in Computer Science, Machine Learning, or related field, or equivalent practical experience.
Preferred Qualifications
Proficiency in machine learning libraries (transformers, datasets).
Strong problem-solving and collaboration skills, with the ability to learn quickly and adapt to production-grade systems.
Experience working with Multi-modal LLMs to enable Voice capabilities is a plus or prior experience with STT, TTS systems.
Experience with deploying to cloud environments (AWS, GCP, on-remote hybrid) is required.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Apple accepts applications to this posting on an ongoing basis.