JobsMachine Learning Video Processing Engineer
Job description
The machine learning video processing engineer role at Apple involves working with a dynamic team to develop innovative image and video processing technologies. This position focuses on creating machine learning algorithms optimized for resource-constrained environments. The engineer will collaborate with other Apple engineers and contribute to projects that impact a billion users. A strong background in video processing and compression technologies is essential for success in this role.
Requirements
- Bachelor's degree in Computer Science, Electrical Engineering, or a related major.
- A minimum of 3 years of relevant industry experience.
- Familiarity with Signal Processing, Machine Learning, CPU architecture, and Operating Systems.
- Proficiency in Python, Java, or C/C++ programming.
- Experience with performance optimization, including GPGPU SIMD programming.
- Knowledge of deploying neural networks to hardware.
- Experience with multithread NEON / SIMD.
- Familiarity with GPU APIs such as Metal, CUDA, OpenGL, and/or OpenCL.
- Excellent written and oral communication skills.
Responsibilities
- 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.
Benefits
- 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.
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