Machine Learning Engineer, Proactive - Large Language Models, Generative AI & Agentic Systems

We are in search of a driven Machine Learning Engineer who has a strong understanding of LLMs and Generative AI and is excited to explore the rapidly evolving landscape of LLM-powered agents, tool-use models, and advanced reasoning techniques. You will help translate groundbreaking research into production systems, influence our technical direction, and shape the future of AI at Apple.

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Strong experience in Machine Learning, with emphasis on LLMs, Generative AI, or large-scale deep learning systems.
• Demonstrated ability to read, interpret, and apply cutting-edge research to real-world engineering problems.
• Experience with model training, fine-tuning, or building scalable ML systems.
• Strong programming and problem-solving skills., * Familiarity with agentic AI, structured tool-use models, or multi-turn reasoning systems. (Not required-experience is a plus, and interest in the domain is highly valued.)
• Hands-on experience with end-to-end LLM development: dataset curation, fine-tuning, evaluation, prompt optimization, or model hosting.
• Published research demonstrating contributions to LLMs, Generative AI, or related subfields.
• Ability to guide technical direction, mentor others, and collaborate effectively in a fast-paced environment.

The Intelligence Platform team empowers clients across Apple's operating systems with high-quality, user-centric knowledge and inferences that enable next-generation user experiences. We're an applied Machine Learning team that leverages state-of-the-art technologies-Generative AI, Large Language Models, RAG based systems, and emerging agentic AI patterns-to deliver high-quality inferences at scale!