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Apple AIML - Machine Learning Researcher Foundation Models United States, New York, New York 633484789
01.06.2024
Description
We believe that the most interesting problems in deep learning research arise when we try to apply learning to real-world use cases, and this is also where the most important breakthroughs come from. You will work with a close-knit and fast-growing team of world-class engineers and scientists to tackle some of the most challenging problems in foundation models and deep learning, including natural language processing, multi-modal understanding, and combining learning with knowledge. Example applications include (but are not limited to): Further, you will have opportunities to identify and develop novel applications of deep learning in Apple products. You will see your ideas not only published in papers, and also improve the experience of millions of users.
Key Qualifications
- Demonstrated expertise in deep learning with publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech) or a track record in applying deep learning techniques to products
- Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow
- Ability to work in a collaborative environment.
Education & Experience
PhD, or equivalent practical experience, in Computer Science, or related technical field.
Pay & Benefits
- 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 $138,900 and $208,300, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.
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