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Apple Inc. in Seattle, WA is seeking a Machine Learning Engineer to build end-to-end pipelines and production systems that turn multimodal foundation models into shipping Apple Intelligence features.
You will own data curation, training pipelines, fine-tuning, evaluation, and deployment under real latency and privacy constraints, collaborating across modeling, platform, and hardware teams to deliver market-leading AI experiences.
Seattle, Washington, United States Hardware
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Multifaceted, amazing people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us in this truly exciting era of Artificial Intelligence to help deliver the next groundbreaking Apple products and experiences!The Multimodal Intelligence team builds and ships the Computer Vision and Machine Learning systems behind Apple Intelligence — spanning data collection and curation, training and fine-tuning, evaluation, optimization, and on-device deployment. Our team has an established track record of delivering features that combine Apple's sensing hardware with large foundation models, including Visual Intelligence and the on-device foundation models that power text and visual understanding across iPhone, iPad, Mac, and Apple Vision Pro. We are focused on building experiences where a device can see, read, and reason about the world around it — privately, responsively, and on-device wherever possible.
We are looking for a Machine Learning Engineer to build the pipelines, infrastructure, and production systems that turn multimodal foundation models into shipping Apple Intelligence features. You will own end-to-end model delivery: building and scaling data curation and training pipelines, fine-tuning and optimizing large multimodal models for on-device and hybrid execution, standing up reproducible evaluation and regression testing for text and visual understanding, and hardening promising approaches into robust, maintainable production systems under real latency, memory, power, and privacy constraints.You will work closely with modeling, platform, hardware, and product engineering teams across Apple — taking future hardware design and product needs into account as you make implementation decisions — and you will have the opportunity to collaborate broadly to deliver the best possible products.
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 $142,300 and $263,300, 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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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.
We believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.