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Apple Machine Learning Researcher Multimodal Foundation Models United States, Washington, Seattle 909776110
21.12.2024
Description
This position requires a highly motivated person who wants to help us advance the field of generativeAI and multi-modal foundation models. You will be responsible for designing, implementing, evaluating foundation models based on the latest advancements in the fields, taking into account future hardware design and product needs. In addition, you will have an opportunity to engage and collaborate with several teams across apple to deliver the best products.
Minimum Qualifications
- Experience in developing, training/tuning multimodal LLMs
- Programming skills in Python and C++
- Bachelors Degree and a minimum of 3 years relevant industry experience.
Key Qualifications
- Strong academic and publication record (CVPR, ICCV/ECCV, NeurIPS, ICML, etc)
- Solid programming skills with Python
- Deep understanding of large foundation models
- Deep understanding of multi-task, multi-modal machine learning domain
- Familiarity with deep learning toolkits
- Familiar with challenges associated with training large models and working with large data
- Ability to communicate the results of analyses in a clear and effective manner
Education & Experience
PhD in Computer Science, Computer Vision, Computer Graphics, Machine Learning or equivalent.
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 $166,600 and $296,300, 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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