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Apple Applied Research Engineer - Multimodal LLMs United States, California, Sunnyvale 252828124
04.07.2024
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Description
• Conduct research and development on multimodal large language models, focusing on exploring and utilizing diverse data modalities• Design, implement, and evaluate algorithms and models to enhance the performance and capabilities of our AI systems• Collaborate with cross-functional teams, including researchers, data scientists, software engineers, to translate research into practical applications• Stay up-to-date with the latest advancements in AI, machine learning, and computer vision, and apply this knowledge to drive innovation within the company
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.
Preferred Qualifications
- Expertise in one or more of: computer vision, NLP, multimodal fusion, Generative AI.
- Experience with at least one deep learning framework such as JAX, PyTorch, or similar.
- Publication record in relevant venues.
- PhD in Computer Science, Electrical Engineering, or a related field with a focus on AI, machine learning, or computer vision.
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 $256,500, 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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