The Machine Learning Engineer role at Apple involves working with the Productivity Apps team to develop innovative productivity tools. This position focuses on building state-of-the-art generative models and applications that enhance user experiences. The engineer will collaborate with a diverse team of creatives, designers, and engineers to drive features from concept to delivery. This is a highly impactful opportunity for someone passionate about generative modeling and sustainable software development.

• MS + 2 years of industry experience or PhD in Computer Science, Computer Vision, Machine Learning, or related field with publications in generative models.
• Hands-on experience training generative models such as diffusion models, GANs, VAEs, or autoregressive image models.
• Strong programming skills in PyTorch or JAX.
• Experience with compositional or layout-conditioned image generation, or image decomposition/editing.
• Experience deploying models to memory or compute constrained environments.
• Experience with large-scale model training and parallelization.
• Track record of publications in top-tier machine learning or computer vision conferences.

• Build state-of-the-art generative models and applications.
• Partner with cross-functional teams to deliver end-to-end features.
• Drive features from concept all the way to delivery.
• Collaborate effectively with all levels of the organization.

• 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.