The Machine Learning Engineer role at Apple focuses on developing conversational and generative AI systems that prioritize user privacy and responsiveness. The position involves working at the intersection of machine learning research and product engineering, rapidly iterating on ideas and translating them into scalable systems. The engineer will collaborate with cross-functional teams to create features that enhance conversational understanding and personalization for Apple's Vision devices. This role requires balancing experimentation with execution to ensure high standards of reliability and user experience.

• PhD with 3+ years or MS with 5+ years of relevant experience in AI/ML, Computer Science, Electrical Engineering, or a related field.
• Strong experience with deep learning, particularly in natural language processing and/or multimodal models.
• Hands-on experience with modern generative AI systems and computer vision models, including prompt design, fine-tuning, and evaluation.
• Familiarity with ranking, retrieval, and personalization algorithms.
• Proficiency in Python and experience with ML frameworks such as PyTorch, with TensorFlow being a plus.
• Experience integrating ML models into production systems.
• Strong communication skills and the ability to collaborate across disciplines.
• Curiosity, pragmatism, and a product-oriented mindset.
• Experience with conversational AI systems or interactive ML-driven experiences.
• Exposure to multimodal or embodied AI systems, including voice, animation, agents, or real-time interaction.
• Familiarity with Apple platforms, frameworks, or ML infrastructure.
• Evaluation-based measurement expertise using eval frameworks to measure non-deterministic experiences for consumer-facing products.

• Design, prototype, and deploy ML-driven features that enhance conversational and generative experiences.
• Collaborate closely with researchers, product managers, designers, and platform engineers to define problems and iterate on solutions.
• Integrate modern model architectures into production frameworks used at scale.
• Balance experimentation with execution by moving quickly when exploring new ideas and rigorously when transitioning work into production.

• 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.