Machine Learning Research Scientist - Health AIML
Apple
26 days ago
On-site
Seattle, Washington, United States
The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers" lives.
We’re developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple.\\n\\nWe are looking for a research lead to guide multimodality research. You will lead the development of foundational technology that enables models to understand health and fitness data.
Lead research into health and fitness representation models and multimodal models.\\nDesign, prototype and scale up new architectures to improve model intelligence.\\nExecute and analyze experiments autonomously and collaboratively.\\nStudy, debug, and optimize model performance and computational performance.\\nContribute to training and inference infrastructure.\\nGuide technical and architectural decision.
PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.\\nIndustry work experience.\\nExperience landing contributions to major LLM training runs.\\nProven track record of publishing SOTA.\\nStrong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
Experience in training and evaluating multimodal models.\\nUnderstand of time-series modeling, self-supervised learning, and cross-modal training.\\nAbility to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.\\nMotivated by safely deploying LLMs in the health and fitness space.
We’re developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple.\\n\\nWe are looking for a research lead to guide multimodality research. You will lead the development of foundational technology that enables models to understand health and fitness data.
Lead research into health and fitness representation models and multimodal models.\\nDesign, prototype and scale up new architectures to improve model intelligence.\\nExecute and analyze experiments autonomously and collaboratively.\\nStudy, debug, and optimize model performance and computational performance.\\nContribute to training and inference infrastructure.\\nGuide technical and architectural decision.
PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.\\nIndustry work experience.\\nExperience landing contributions to major LLM training runs.\\nProven track record of publishing SOTA.\\nStrong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
Experience in training and evaluating multimodal models.\\nUnderstand of time-series modeling, self-supervised learning, and cross-modal training.\\nAbility to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.\\nMotivated by safely deploying LLMs in the health and fitness space.