Job Description

Creator Studio is building agentic intelligence inside Apple's professional creative apps. We aim for machine intelligence to assist and enhance creators’ intent and vision, complementing creators rather than replacing it. This team has unusual leverage: our work spans many apps, and getting a capability right lifts a whole family of professional creative tools at once.

The team is established and growing. We're looking for ML engineers who want to define the product. That means less time on models in isolation and more on the experiences they make possible, working next to the designers, quality teams, app teams, and engineers who own the workflows.

You work where a frontier model meets the real depth of a professional creative app. The job is to make that meeting useful. A model's raw capability is not yet a feature, and turning it into something that helps inside a real project and holds up well enough to ship is most of what you'll do. Creative work is open-ended. That makes it hard to do well, and hard to measure. So you'll spend as much time on evaluation, prompting, and the tools and skills a model reaches for as on the models themselves.

The best creative software makes someone more capable while leaving them in charge. That balance is the hard part. The assistant should help a person move faster and push an idea further, with the craft still theirs, and getting it right is a product question as much as a modeling one. It sits at the center of this role.

Preferred Qualifications

Experience building agentic systems, LLM tool-use / function-calling, or evaluation harnesses.
Deep, hands-on experience as a professional or power user of creative tools — DAWs, NLEs, image editors, office productivity apps, or design suites. You know these workflows from the inside, and you have a point of view about what helps a creator and what gets in the way. Experience with Apple's own creative apps is not required.
We welcome non-traditional backgrounds: demonstrated product judgment and creative-domain expertise can matter as much as a conventional Computer Science or ML resume.
Strong programming skills in Python and experience with deep-learning toolkits like PyTorch, JAX, or TensorFlow.
Experience optimizing models and algorithms to run efficiently on resource-constrained / on-device platforms such as Core ML.
Experience with Swift and iOS/macOS development.
A record of publications or patents in relevant areas.

Minimum Qualifications

3+ years developing and shipping reliable, maintainable, testable code, or equivalent demonstrated experience.
Hands-on experience applying LLMs / foundation models or multimodal ML to real products or projects, e.g. prompting, fine-tuning, retrieval, evaluation, or agentic systems.
Strong intuition for experimental design and a repertoire of statistical techniques to measure genuine effects from noise.
A strong product sense: the judgment to ask not only "can the model do this?" but "is this the right experience?"
Ability to work effectively in a fast-paced environment and to communicate clearly with technical and non-technical partners.
Bachelor's degree in Computer Science or a related field, or equivalent practical experience.