The Machine Learning Engineer will join Apple's AI and Machine Learning organization, focusing on innovative research in foundation models, particularly with audio data. This role involves collaboration with machine learning researchers, engineers, and data scientists to tackle ambitious technical challenges. The engineer will work across the full ML pipeline, from pre-training on large-scale audio corpora to fine-tuning with task-specific datasets. The position offers opportunities to publish and present groundbreaking research at premier academic venues.

• 5+ years of experience developing and evaluating ML applications.
• Deep technical skills in one or more machine learning areas such as computer vision, audio, or natural language processing.
• Strong software development skills with proficiency in Python.
• Hands-on experience with deep learning toolkits like PyTorch, TensorFlow, or JAX.
• Demonstrated publication records in relevant conferences such as CVPR, ICCV, or NeurIPS.

• Design and develop a comprehensive multi-modal data generation and curation framework for foundation models.
• Contribute to building robust model evaluation pipelines that support continuous improvement.
• Analyze multi-modal data to understand its influence on model behavior and outcomes.
• Design self-supervised and semi-supervised representation learning pipelines for tasks like speech recognition.
• Apply data selection techniques to improve data efficiency and reduce distributional gaps.

• 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.