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AI Research Scientist
Apple
- Sunnyvale, California, United States
- Sunnyvale, California, United States
Über
Description
You will work on advancing the capabilities of foundation models and guiding them toward real-world applications in Apple products. This includes researching and developing methods that improve alignment, reasoning, and adaptation of large models to practical use cases, while ensuring they meet Apple's standards for efficiency, scalability, and privacy. You will focus on creating customized foundation models with targeted capabilities that operate efficiently in constrained environments, supporting the next generation of intelligence across Apple's ecosystem.
Your work includes staying ahead of emerging research and identifying techniques that are suitable for real-world deployment, helping translate scientific advancements into production-quality solutions. You will design and optimize large-scale data pipelines that support robust training and detailed evaluation of foundation models, working with massive multimodal datasets to push the limits of performance. You will explore new techniques that strengthen focused reasoning, multimodal understanding, and adaptive behavior, enabling models that perform well at large scale while also being tailored for specific Apple experiences, from cloud systems to on-device intelligence.
Collaboration is essential in this role. You will partner with multi-functional teams of engineers and researchers to bring customized and efficient models into Apple products, ensuring smooth integration and enabling intelligent and natural user experiences throughout the ecosystem.
Minimum Qualifications
Proficient programming skills in Python and experience with at least one modern deep learning framework (PyTorch, JAX, or TensorFlow).
Experience working with large-scale training pipelines and distributed systems.
MS in Computer Science, Computer Vision, Machine Learning, or related technical field, and a minimum of 6 years relevant experience.
Preferred Qualifications
PhD, or equivalent practical experience, in Computer Science, Machine Learning, or a related technical field.
Demonstrated expertise in related field with publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV,COLM, etc).
Experience with full stack of foundation model training (vision-language).
Familiarity with large-scale data pipelines, including data curation, preprocessing, and efficient storage.
Ability to work effectively in a multi-functional, collaborative environment.
Experience with advanced reasoning or reinforcement learning methods.
Experience with model distillation using on-policy or off-policy techniques.
Sprachkenntnisse
- English
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