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Apple Machine Learning Engineer OS Intelligence United States, Washington, Seattle 181544733
14.04.2025
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The team is looking for extraordinary candidates to design Deep Learning architectures, implement industry-leading Machine Learning algorithms, as well as contribute high-quality software to iOS, iPadOS, macOS, watchOS, visionOS, and more. In this unique and highly visible role, you will be working cross-functionally to add intelligence to new domains to create beautiful user experiences. Through data analysis, ML model development, and on-device software development, you will push the boundary of what's possible in an operating system.
In this role, you will have the opportunity to:-Innovate, conceptualize, and prototype novel intelligent experiences by leveraging recent advances in LLMs, sequence-to-sequence models, and fine-tuning (like LoRA adapters, RAG pipelines) to architect foundation models for a diverse set of applications in the OS.-Build scalable cloud-based and on-device infrastructure to accelerate seamlessly running experiments and monitoring shipped models.-Analyze, understand, and present key performance data for highly-visible OS features.-Write elegant, performant code in Objective-C or Swift and test, debug, and productize it.
- Bachelor’s degree in Computer Science or equivalent work experience.
- Strong programming background and a clear understanding of operating system components.
- Familiarity with statistics, data analysis, or machine learning and the enthusiasm to learn more.
- Highly professional and collaborative with outstanding communication and presentation skills.
- Proven track record leading software projects from inception through customer delivery.
- Ability to deliver high quality work on tight schedules consistently.
- Familiarity with Python, Objective C, or Swift.
- Familiarity with Deep Learning libraries like PyTorch and Tensorflow.
- Experience building and leading Applied Machine Learning projects in industry or academia.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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