Machine Learning Research Engineer - Large Language Models (LLMs), Siri Planner Team

Job Description

Join the Siri Planner team as a Machine Learning Research Engineer and play a pivotal role in shaping the future of virtual assistants by building ground-breaking AI solutions.

Requirements

• Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related quantitative field; or BSc with 2+ years of relevant industry experience
• Hands-on experience in machine learning engineering outside of research
• Strong Python proficiency, including development, debugging, and design, coupled with extensive experience using ML frameworks (e.g. PyTorch, Jax, HuggingFace)
• Excellent problem-solving, critical thinking, and interpersonal skills, with a collaborative attitude

Responsibilities

• Developing innovative systems for synthetic training data generation and implementing strategies for the continuous optimization of model performance
• Designing and implementing agentic workflows and RAG systems to enhance Siri's capabilities
• Optimizing model performance for tool calling and reasoning tasks
• Actively staying at the forefront of academic and industry research in LLMs, NLP, and agentic systems, and translating novel insights into practical solutions
• Collaborating closely with a multidisciplinary team of researchers, software engineers, and product designers to seamlessly integrate AI innovations into the Siri user experience

Benefits

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.