AI Research Scientist: Multimodal Foundation Models - Architecture, Pre-Training & Distillation
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Key details
Why this role is notable
Apple is building its own multimodal foundation models end to end, from architecture and pre-training through distillation, with the explicit goal of fitting them on-device under memory, latency, energy and privacy limits, which signals a bet that frontier-level capability can be delivered locally rather than only through cloud APIs.
Job Description
The Multimodal Intelligence Team is building the next generation of foundation models for Apple experiences. We are looking for a research scientist to advance the architectures, pre-training methods, and distillation techniques that make highly capable multimodal models practical across the Apple ecosystem.
Our research spans the full foundation-model lifecycle: model architecture, pre-training objectives, data mixtures, optimization, scaling, distillation, and evaluation. A defining challenge of our work is to develop models that combine broad intelligence with the memory, latency, energy, and privacy requirements of on-device deployment.
You will have the opportunity to shape new research directions, conduct ambitious experiments at scale, and translate successful ideas into foundation-model technologies that can reach Apple products. Where appropriate, this work may also lead to publications and the open sourcing of selected models, research artifacts, evaluations, or tools.
