Apple has 261 active AI-related job listings. The majority of these roles are focused on agents, accounting for 24% of the total, followed by application (22%) and serving infrastructure (21%). Engineering is the primary function for these positions, with the United States being the dominant hiring country. Frequent tech tags include model serving, inference infrastructure, and LLM observability. Over the last 30 days, Apple has posted 111 new AI roles, representing a 61% increase compared to the previous 30-day period.
Currently tracking 171 active AI roles, down 37% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $120k–$487k (avg $235k).
Apple currently has 233 active AI-related roles in our index. The most common open titles are: Machine Learning Engineer (4), AIML - Sr Data Scientist, Evaluation (2), Advanced Manufacturing Engineer(iPhone) - Smart Manufacturing (2), Machine Learning Engineer, Apple Services Engineering (2), Machine Learning Software Engineer (2). Most positions are in Engineering and Research.
Apple's active AI hiring is concentrated in: agents (30%), application (21%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Apple is hiring AI talent in: United States (182 roles), China (17 roles), India (10 roles), United Kingdom (7 roles).
Job postings at Apple most frequently mention: Machine Learning, Python, Data Science, Large Language Models (LLMs), Statistics.
In the past 30 days, Apple has posted 80 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team at Apple Media Services. The role involves evaluating and optimizing Foundation Models and generative AI systems, architecting evaluation frameworks, designing MLOps pipelines, and translating failure modes into guardrails and training signals. This position bridges human perception and algorithmic performance, working cross-functionally to ensure AI experiences are reliable, safe, and aligned with human expectations. | Eval GatePost-train | 9 |
| Machine Learning Engineer Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team. This role involves architecting evaluation frameworks, designing MLOps pipelines for model assessment, and translating qualitative failure modes into programmatic guardrails and training signals for Foundation Models and generative AI systems. The role also involves collaborating with various teams to ensure AI experiences are reliable, safe, and aligned with human expectations. |
| Eval GatePost-train |
| 9 |
| Applied Machine Learning Engineer - Developer Publications Applied Machine Learning Engineer focused on building and maintaining LLM evaluation pipelines for developer tools at Apple. The role emphasizes MLOps/LLMOps, assessing model quality, tracking regressions, and supporting continuous improvement cycles, requiring strong engineering fundamentals and LLM evaluation experience. | Eval GatePost-train | 8 |
| Senior Software Engineer - Siri Agentic Evaluation Platform The role involves building software platforms and tools for evaluating Siri's quality and effectiveness using agentic technology. The primary focus is on creating evaluation platforms that provide feedback signals throughout the software lifecycle, with a secondary focus on the agentic technology itself. | Eval GateAgent | 7 |