AIML - Machine Learning Engineer, Foundation Models

Apple is revolutionizing artificial intelligence by developing sophisticated foundation models that power intelligent features across our product ecosystem. We're seeking skilled Machine Learning Engineers to transform cutting-edge research into scalable, production-ready AI solutions. We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products., Apple Foundation Model Team are a group of engineers and researchers responsible for building foundation models at Apple. We build infrastructure, datasets, and models with fundamental general capabilities such as understanding and generation of text, images, speech, videos, and other modalities and apply these models to Apple products. We are looking for MLEs who are passionate about developing algorithms, techniques, and systems that push the frontier of deep learning and delight billions of users with Apple products powered by foundation models. We are looking for an exceptional Machine Learning Engineer to design, develop, and deploy foundation models that drive intelligent features across Apple's product portfolio. You will bridge the gap between research and production, transforming advanced AI concepts into robust, performant systems that enhance user experiences.

• MS or PhD in Computer Science, Machine Learning, or related technical field

• Expert-level programming skills in Python

• Proficiency in machine learning frameworks such as Jax, PyTorch, TensorFlow

• Strong background in: Distributed training, Model optimization, and Machine learning infrastructure

• Experience with large-scale model training and deployment

• Familiarity with: Kubernetes, Docker, Cloud platforms (AWS, GCP, Azure)

• Distributed computing frameworks

Preferred Qualifications

• Experience with foundation models and large language models

• Background in multi-modal AI systems

• Demonstrated ability to transform research prototypes into production systems

• Published research or significant contributions to open-source ML projects

• Understanding of on-device machine learning techniques