About the position
Join Apple’s Information Systems and Technology (IS&T) organization, the engine behind everything Apple does for customers and for the people who build for them. IS&T supports 2.5 billion active Apple devices, processes billions of secure transactions, and keeps the technology that defines modern life running flawlessly. Customer Systems, part of IS&T, drives the technology behind Apple's customer support experience, from contact center operations to the software powering the Genius Bar. The team also builds and operates AppleCare's online support platform, handling 6 billion visits per year. The Customer Systems - Gen AI Solutions team is responsible for building multi-turn, conversational, agentic LLM-based applications and frameworks to support Apple customers across numerous lines of business. This role involves hands-on contribution to a team of engineers, data scientists, and researchers to enhance a multi-modal, multi-agent platform, focusing on incorporating the latest models and advancements to improve latency, cost, and customer experience. This is an opportunity to contribute innovation and research to a well-established generative AI platform within Apple, with significant opportunities for growth.
Responsibilities
• 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-round agentic solutions for conversational knowledge-intensive tasks.
• Partner with data and platform engineers to ensure scalable deployment and monitoring.
• Stay current with advancements in large language modeling, vector search, RAG, and LLM Agents.
• Participate in architecture discussions with engineers and partner teams.
• Collaborate with product and business stakeholders to incorporate customer experience requirements into AI solutions.
• Support localization and rollout of AI features across multiple markets.
Requirements
• 8+ 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
• Exposure to multi-agent orchestration frameworks in Rust and Python.
• Familiarity with modern deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience with data preprocessing, tokenization, and pipeline automation.
• 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 with deploying to cloud environments (AWS, GCP, on-remote hybrid) is required.
• Fluency in written and spoken Chinese to support Greater China market
• Bachelor's or Master's degree in Computer Science, Machine Learning, or related field, or equivalent practical experience.
• Strong experience partnering with business and engineering teams to deliver AI solutions.
Nice-to-haves
• Experience working with Multi-modal LLMs to enable Voice capabilities is a plus or prior experience with STT, TTS systems.