The machine learning video processing engineer will work within a dynamic team at Apple, focusing on developing innovative image and video processing technologies. This role requires a self-motivated engineer who thrives in a technically challenging environment. The team is responsible for creating core technologies that enhance Apple products and services. The engineer will engage in projects that leverage machine learning to optimize video processing in resource-constrained environments.

• A Master's degree in Computer Science, Electrical Engineering, or a related major is required.
• Familiarity with Signal Processing, Machine Learning, CPU architecture, and Operating Systems is essential.
• Proficiency in programming languages such as Python, Java, or C/C++ is necessary.
• Experience with performance optimization techniques, including GPGPU SIMD programming, is required.
• Knowledge of deploying neural networks to hardware is essential.
• Experience with multithread NEON / SIMD is required.
• Familiarity with GPU APIs, preferably Metal, CUDA, OpenGL, and/or OpenCL, is necessary.
• Excellent written and oral communication skills are required.

• Develop, implement, and optimize machine learning-based video processing algorithms.
• Work on data collection and pre-processing for training, testing, and validation.
• Investigate the latest learning-based low-level vision technologies and tasks.

• 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.