The System Intelligence Machine Learning (SIML) organization is seeking Research Engineers with expertise in Machine Learning and Computer Vision to advance multi-modal Human Sensing technologies. This role involves developing AI/ML models for identity recognition systems that enhance user experiences across Apple platforms. The team focuses on building foundation models for facial and full-body perception, contributing to innovations in areas like personalized search and photography. Candidates will engage in a fast-paced environment, driving impactful research and development.

• Master's or Ph.D. in Computer Science, Computer Engineering, or related fields, or equivalent professional experience in Computer Vision and Machine Learning research and development.
• Proven track record of training, fine-tuning, and evaluating deep learning models for vision tasks using modern ML architectures.
• Background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful software developments.
• Proficient in Python, PyTorch, or equivalent deep learning frameworks.
• Expert-level knowledge of state-of-the-art methods in face recognition or other facial analysis and biometric systems.
• Hands-on experience training and scaling multi-modal large language models or large-scale vision-language models.
• Experience with on-device ML, model optimization, or production-grade ML pipelines.

• Design, implement, and deploy state-of-the-art visual recognition systems.
• Build foundation models for facial and full-body perception.
• Drive data quality excellence through strategic dataset curation, validation, and generation to support model development.
• Build tools and frameworks for systematic failure analysis, identifying edge cases, and driving continuous model improvement.
• Interact with cross-functional stakeholders to gather product requirements and translate these into actionable plans for ML research and development.
• Communicate results and insights to partners and senior leaders, providing clear and actionable recommendations.
• Stay current with the latest trends, technologies, and methodologies in machine learning, multi-modal foundation models, computer vision, and natural language understanding.
• Contribute to Apple's ML community by disseminating research ideas and results, enhancing shared infrastructure, and mentoring fellow practitioners.

• 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.