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Apple Machine Learning Engineer United States, Washington, Seattle 794816959
07.04.2025
APPLE INC has the following available in Seattle, Washington. Prototype, develop and experiment with computer vision techniques for search and generative artificial intelligence (AI). Define and measure objective metrics for algorithmic system performance. Understand product requirements and translate them into engineering goals and tasks. Utilize applied computer vision and engineering to create new experiences. Guide data collection and labelling for train and test data sets along with defining quality gates. Build machine learning model training solutions and run systematic experiments to improve performance. Build systems for an end-to-end production grade stack that is capable of achieving low latency and high throughput. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $145,611 - $204,000/yr and your base pay will depend on your skills, qualifications, experience, and location.
- Experience and/or education must include:
- Master’s degree or foreign equivalent in Computer Science or related field.
- Using Python or C++ to write software that will be a part of search, generative AI, or machine learning systems.
- Utilizing modern machine learning and computer vision techniques involving deep learning for object segmentation, detection, recognition, or generation.
- Leveraging deep learning frameworks including PyTorch or TensorFlow to build and experiment with computer vision and machine learning models.
- Applying knowledge from academic or industrial research to improve computer vision models (eg: for search, object recognition, or video applications).
- Using industrial or consumer grade computer vision systems and the key components involved for optimal end-to-end performance and reliability.
- Data structures and algorithms to author functionally correct and optimal computer programs for search and similar applications.
- Testing, debugging and improving computer programs to achieve functional correctness for a given task.
- Knowledge of computer system design (or knowledge of the interaction between modules), including leveraging components (or libraries) to build complex systems.
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