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Job Description
Weekly Hours: 40
Role Number: 200625177-3337
Summary
The Science Model Optimization and Algorithms Development team brings innovative AI research into Apple products.
Description
We are looking for strong ML applied scientists and engineers to build server-based and on-device large machine learning capabilities tailored for Apple Silicon. We are part of a collaborative group of software developers and deep learning experts working in the area of neural network optimization and related algorithms. Successful candidates will have a strong software engineering background, zero-to-one machine learning development experience, and broad expertise in machine learning model optimization (quality optimization, performance optimization, etc).
Minimum Qualifications
Experience on developing/optimizing/training large language models (LLMs), or large computer vision models, or generative AI models
Software engineering skills in Python and general purpose system admin and infrastructure management abilities
History of applied research in neural network model optimization or training or a related area application
Proven track record to drive scientific investigations and experiments and overcome obstacles and uncertainty in a research environment
MS degree and 3+ years of proven experience
Preferred Qualifications
Publication record at top AI/ML venues
Experience with network optimization algorithms, e.g. quantization and compression, sparsification, knowledge distillation, or NAS
Experience with languages such as C/C++, Java, Go, Swift, Rust, or Obj-C
Infrastructure management and debugging experience
Experimental rigor when training/evaluating DNNs for the purpose of benchmarking neural network optimization algorithms
Strong communication and accountability skills; hard-working, strong work ethic, and collaboration abilities
PHD in related field
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .
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