This role pays less than
62%
of similar roles. Most pay
$189,737–$254,750
— the shaded band above.
At the midpoint, this role pays about
$203k
versus about
$222k
for comparable roles.
Based on 240 similar postings.
Employer
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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
As an ML Engineer - Creator Studio, you will join a growing team building agentic intelligence within professional creative apps to enhance creator intent and vision. You will design, build, and evaluate agentic AI capabilities by transforming frontier model capabilities into reliable product behaviors through agentic architecture, tool design, and structured outputs. Your daily work involves developing rigorous evaluations for open-ended creative tasks, investigating model failures end-to-end, and collaborating with designers and domain experts to translate workflows into features. You will work with on-device and server foundation models while optimizing for on-device inference constraints. Required skills include Python, PyTorch, JAX, or TensorFlow, along with experience in LLMs, multimodal ML, prompting, fine-tuning, and retrieval. The role focuses on the technical challenge of integrating machine intelligence into complex creative workflows to assist users without replacing their personal craft.
Design and build agentic AI capabilities to help users complete tasks in professional creative apps.
Convert raw frontier model capabilities into reliable product behaviors using agentic architecture and structured outputs.
Develop rigorous evaluation metrics for open-ended, hard-to-score creative tasks to drive system improvements.
Optimize on-device and server foundation models for the specific constraints of mobile and desktop hardware.
Investigate and debug model failures from the user-facing symptom down to the underlying technical cause.
Translate complex creative workflows into functional features by collaborating with designers and domain experts.
What we're looking for
3+ years of experience developing and shipping reliable, maintainable, and testable code or equivalent demonstrated experience.
Hands-on experience applying LLMs, foundation models, or multimodal ML to products through 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.
Strong product sense to determine if model capabilities translate into the right user experience.
Ability to communicate clearly with both technical and non-technical partners in a fast-paced environment.
Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
Experience building agentic systems, LLM tool-use/function-calling, or evaluation harnesses (preferred).
Deep experience as a power user of creative tools, strong Python skills with PyTorch/JAX/TensorFlow, and on-device optimization experience (preferred).
LLMs
Foundation Models
Agentic Systems
Python
PyTorch
JAX
TensorFlow
Core ML
Swift
iOS
macOS
Fine-tuning
Retrieval
Evaluation Harnesses
On-device Inference
Multimodal ML
Machine Learning
LLMs
Foundation Models
Agentic Systems
Python
PyTorch
JAX
TensorFlow
Core ML
Swift
iOS
macOS
Prompting
Fine-tuning
Retrieval
Evaluation
Multimodal ML
On-device Inference