Machine Learning Engineering Intern, Personal Agentic Search
Role Overview
The Personal Agentic Search team builds AI-powered agents that understand a person's context, reason over personal data, and retrieve information while preserving user privacy.
As an intern, help build and evaluate machine learning systems behind these experiences and contribute to features used by Apple customers.
The internship sits at the intersection of natural language processing, large language models, and information retrieval.
Key Skills for This Role
Full Job Posting
Team and role
The Personal Agentic Search team builds AI-powered agents that understand a person's context, reason over personal data, and retrieve information while preserving user privacy.
As an intern, help build and evaluate machine learning systems behind these experiences and contribute to features used by Apple customers.
The internship sits at the intersection of natural language processing, large language models, and information retrieval.
Work and responsibilities
- Work on real projects alongside experienced engineers and researchers.
- Help turn research ideas into robust, user-facing experiences.
- Help build and evaluate machine learning systems for personal agentic search.
Minimum qualifications
- Currently pursuing a BS, MS, or PhD in Computer Science, Machine Learning, or a related field.
- Strong computer science foundation, including data structures, algorithms, and software design.
- Proficiency in at least one programming language such as Python, Swift, C++, or Java.
- Solid machine learning foundation and working knowledge of NLP fundamentals, including tokenization, embeddings, language modeling, and text classification; experience may come from coursework, research, personal projects, or professional work.
- Strong communication and collaboration skills and interest in working in a team.
Preferred qualifications
- Familiarity with LLM architectures such as Transformers and attention mechanisms and how they are trained and applied.
- Familiarity with search and retrieval algorithms, including indexing, ranking, nearest-neighbor search, and relevance evaluation.
- Experience with agentic LLM workflows such as planning, tool calling, and multi-step reasoning.
- Experience with on-device machine learning or privacy-preserving machine learning.
- Experience designing experiments, metrics, and datasets to evaluate model or search quality.
- Proficiency in more than one of Python, Swift, and C++.
Company context
Apple describes accessibility and inclusion as important to its workplace and says it will consider reasonable accommodations for applicants.
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