ML Engineer, Creator Studio

Apple Inc

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Work type: On-site
Location: Cary, NC
Posted: 70 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $225k

$155k $291k

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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TL;DR · ML Engineer, Creator Studio

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ML Engineer - Creator Studio joins the Creator Studio team to build agentic intelligence within professional creative applications. You will design, build, and evaluate agentic AI capabilities that translate frontier model power into reliable product behaviors. Day-to-day responsibilities include developing agentic architectures, designing tools and skills, and creating rigorous evaluations for open-ended creative tasks. You will work with on-device and server foundation models, optimizing for on-device inference constraints. The role requires proficiency in Python and deep-learning toolkits like PyTorch, JAX, or TensorFlow, along with experience in LLMs, prompting, fine-tuning, and retrieval. You will solve the technical challenge of integrating machine intelligence into complex creative workflows, ensuring models enhance user intent across a family of professional tools while maintaining the user's craft and control.

Skills

LLMs Foundation Models Agentic Systems Python PyTorch JAX TensorFlow Core ML Swift iOS macOS Fine-tuning Retrieval Prompting Evaluation Multimodal ML On-device Inference

What you'll do

Design and build agentic AI capabilities to help users complete tasks in professional creative apps.
Convert frontier model capabilities into reliable product behaviors using agentic architecture and structured outputs.
Develop rigorous evaluation metrics and quality measures for open-ended creative tasks to drive system improvements.
Optimize on-device and server foundation models to run efficiently within hardware constraints.
Perform end-to-end investigations into model and agent failures to identify underlying root causes.
Translate real-world creative workflows into technical capabilities by partnering with designers and domain experts.

What we're looking for

3+ years of experience developing and shipping reliable, maintainable, and testable code.
Hands-on experience applying LLMs, foundation models, or multimodal ML to real products or projects.
Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
Strong intuition for experimental design and a repertoire of statistical techniques to measure genuine effects from noise.
Ability to communicate clearly with technical and non-technical partners in a fast-paced environment.
Strong programming skills in Python and experience with deep-learning toolkits like PyTorch, JAX, or TensorFlow (preferred).
Experience building agentic systems, LLM tool-use, or evaluation harnesses (preferred).
Experience optimizing models for resource-constrained or on-device platforms such as Core ML (preferred).

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