AIML - Machine Learning Engineer, Foundation Models

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.

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.

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)
• 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

Pay & Benefits:

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.