Multimodal Machine Learning Researcher

Socket.dev; Cupertino (CA); On-site; USD 250,000 - 380,000; Full time

Job summary

Apple is seeking a senior technical leader to architect and deploy production-scale multimodal ML within the Scene Understanding domain. You will oversee training of 2D/3D vision-language models on distributed backends and guide on-device deployment of compact architectures, while shaping private, user-centric learning policies.

The role requires cross-functional collaboration with ML researchers, software engineers, and hardware/design teams to push the boundaries of on-device experiences and

Qualifications

• MS or PhD in CS or a related field or equivalent experience.
• Hands-on experience training LLMs or adapting LLMs for downstream tasks.
• Experience at the intersection of NLP and vision for multimodal models.
• Proficiency with ML toolkits (e.g., PyTorch) and Python.

Responsibilities

• Train large-scale multimodal models on distributed backends.
• Deploy compact neural architectures efficiently on device.
• Learn privacy-preserving policies personalized to users.
• Collaborate with ML researchers, software engineers, and hardware/design teams.
• Advance on-device scene understanding and generation capabilities.

Skills

LLM training

NLP & vision

Python

PyTorch

Distributed training

Multimodal ML

Education

MS/PhD in CS or related field

Tools

PyTorch

C/C++

ObjC

Job description

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 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)

Description

We are looking for a candidate with a proven track record in applied ML research. Responsibilities in the role will include training large scale multimodal (2D/3D vision-language) models on distributed backends, deployment of compact neural architectures efficiently on device, and learning policies that can be personalized to the user in a privacy preserving manner. Ensuring quality in the wild, with an emphasis on fairness and model robustness would constitute an important part of the role. You will be interacting very closely with a variety of ML researchers, software engineers, hardware & design teams cross functionally. The primary responsibilities of the role would center on enriching multimodal capabilities of large language models. The user experience initiative would focus on aligning image/video content to the space of LMs for visual actions & multi-turn interactions.

Minimum Qualifications

• M.S. or PhD in Computer Science or a related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience.
• Hands on experience training LLMs/adapting pre-trained LLMs for downstream tasks & alignment
• Modeling experience at the intersection of NLP and vision
• Proficiency in ML toolkit of choice, e.g., PyTorch
• Strong programming skills in Python

Preferred Qualifications

• Familiarity with distributed trainingStrong programming skills in C/C++ or ObjC