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Apple is looking to solve the problem of improving Open Domain Question Answering, Summarization, and the fundamental building blocks of Artificial Intelligence using machine learning and AI-based products and experiences.

Requirements

• Proficiency in a programming language such as Python, Objective-C, C++, Swift, and/or R
• Experience completing a moderate-sized software project
• Academic, research, or industry experience in one of the following: Large Language Models / Generative AI, Machine Learning & ML Research, Natural Language Processing/Conversational AI, Search, or Information Retrieval
• Experience in various pioneering techniques related to LLM fine-tuning
• Supervised Fine-tuning (SFT) with Rejection Sampling
• Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.)
• Parameter efficient fine-tuning techniques (e.g LoRA)

Responsibilities

• Conduct large-scale ML and deep learning research and development
• Improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data)
• Develop sophisticated LLMs to understand user queries, retrieve and rank relevant documents across multiple sources, and synthesize information to provide users with a direct answer
• Research and develop state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications
• Collaborate with researchers and data scientists to develop, fine-tune, and evaluate domain specific LLMs for various tasks and applications in Apple’s AI powered products
• Conduct applied research to transfer the latest research in generative AI to production ready technologies
• Develop and implement safety guardrails for LLMs

Other

• Demonstrated ability to connect and collaborate with others
• Graduate degree in a STEM field or equivalent industry experience in software engineering
• Available to work full-time (40 hours/week) July 13, 2026 - July 9, 2027
• Currently enrolled in a degree program must graduate before this program commences on July 13, 2026
• Submit a cover letter explaining research interests and how they apply to the specific Residency position