The Applied Machine Learning Research Engineer will join the Video Computer Vision group to advance AI and computer vision capabilities. This role focuses on developing and exploring multimodal large language models that integrate diverse data modalities. The team has pioneered real-time human-centric features that enhance user interaction with devices. The engineer will collaborate with multi-functional teams to drive innovation and stay updated on advancements in the field.

• Experience in developing and training multimodal large language models.
• Programming skills in Python.
• Masters degree with a minimum of 3 years relevant industry experience.
• Expertise in one or more of computer vision, NLP, multimodal fusion, or Generative AI.
• Experience with at least one deep learning framework such as JAX, PyTorch, or similar.
• Publication record in relevant venues.
• PhD in Computer Science, Electrical Engineering, or a related field with a focus on AI, machine learning, or computer vision.

• Work on groundbreaking research projects to advance AI and computer vision capabilities.
• Contribute to both foundational research and practical applications on multimodal large language models.
• Design, implement, and evaluate algorithms and models for human understanding.
• Collaborate with researchers, data scientists, software engineers, human interface designers, and application domain experts.
• Stay up-to-date on the latest advancements in AI, machine learning, and computer vision.

• 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.