Senior Multimodal Generative Modeling Research Engineer
4 Months ago • All levels
Research Development
Job Description
The Senior Multimodal Generative Modeling Research Engineer will be a technical leader, experienced in architecting and deploying production-scale multimodal machine learning models. This role involves leading diverse cross-functional efforts, from ML modeling to prototyping and validation. The ideal candidate will possess solid ML fundamentals and an ability to contextualize research contributions within the state of the art. Experience with training and adapting large language models is also essential. The team works on Apple Intelligence technologies and production ML workflows that power features like Spotlight Search, Photos Memories, and Generative Playgrounds. The team also focuses on optimizing and adapting LLMs to best suit on-device user experiences. The engineer will be working to turn cutting edge research into compelling user experiences.
Must Have:
- Experience with architecting and deploying multimodal ML
- Lead cross-functional efforts in ML modeling
- Solid ML fundamentals and knowledge of the state of the art
- Experience with training and adapting large language models
Do you believe generative models can transform creative workflows and smart assistants used by billions? Do you believe it can fundamentally shift how people interact with devices and communicate? Our Scene Understanding team strives to turn cutting edge research into compelling user experiences that realize all these goals and more, working on Apple Intelligence technologies such as Image Playground, Genmoji, Generative Memories, Semantic Search, and many more. We are looking for senior technical leaders experienced in architecting and deploying production scale multimodal ML. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. Solid ML fundamentals and an ability to place research contributions with respect to state of the art would be an essential part of the role. Experience with training and adapting large language models would be an important need. We are the Intelligence System Experience (ISE) team within Apple’s software organization. The team works at the intersection between multimodal machine learning and system experiences. For example, experiences like Spotlight Search, Photos Memories, Generative Playgrounds, Stickers, Smart wallpapers, etc are all areas that the team has had a significant part in delivering through ML core technologies. These experiences that our users enjoy are backed by production ML workflows, which our team works to scale through distributed training. Additionally, our team also focuses on approaches to optimizing and adapting LLMs to best suit on-device user experiences. SELECTED REFERENCES TO OUR TEAM’S WORK: - https://machinelearning.apple.com/research/introducing-apple-foundation-models (https://machinelearning.apple.com/research/introducing-apple-foundation-models) - https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon (https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon) - https://machinelearning.apple.com/research/on-device-scene-analysis (https://machinelearning.apple.com/research/on-device-scene-analysis) - https://machinelearning.apple.com/research/panoptic-segmentation (https://machinelearning.apple.com/research/panoptic-segmentation)
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