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.

Description

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.","responsibilities":"Design and implement scalable, reliable and high-performance machine learning infrastructure for foundation models across text, image, speech, and multi-modal domains

Collaborate with other teams to productionize state-of-the-art AI algorithms

Optimize models for performance, efficiency, and on-device intelligence

Implement machine learning systems with stringent privacy and security requirements

May also be required to manage a small team of engineers.

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

Minimum Qualifications

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)