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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
3515 open roles
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Listed pay typically runs
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The Applied AI Engineer joins the Data Insights organization to build and advance AI-powered platforms for Apple Ads. This role focuses on developing an AI agent platform that connects large language models with internal data infrastructure, analytical tools, and business knowledge to enable natural language querying. You will design scalable systems for agent orchestration, including tool calling, memory, context retrieval, and intelligent routing. Key responsibilities involve building reusable platform components, evaluation frameworks, and monitoring systems to ensure accuracy and reliability. You will utilize Python, machine learning, statistics, and RAG techniques to solve complex business challenges. The work involves transforming emerging AI technologies into practical tools for data access and decision-support, specifically optimizing for scalability, latency, and maintainability within the advertising ecosystem.
Design and build scalable AI agent systems connecting LLMs with data infrastructure, APIs, and analytical tools.
Advance agent orchestration including tool calling, memory, context retrieval, and intelligent routing.
Develop reusable platform components to enable teams to build AI-powered analytical workflows.
Build evaluation frameworks and monitoring systems to improve agent observability, accuracy, and reliability.
Apply machine learning principles to improve retrieval quality, reasoning, and traceability of AI-generated insights.
Develop AI-native solutions from concept to production while optimizing for scalability, latency, and maintainability.
Translate domain expertise and analytical workflows into reusable AI capabilities for business stakeholders.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience.
Experience designing, building, and deploying production software systems with strong Python programming and software engineering fundamentals.
Hands-on experience building and deploying LLM-powered applications using agentic workflows, tool calling, RAG, or related techniques.
Experience with large-scale data platforms or distributed data systems.
Solid foundation in AI, machine learning, statistics, and software engineering principles.
Strong problem-solving, communication, and cross-functional collaboration skills.
Experience architecting and scaling production AI agent platforms, including multi-step orchestration, tool execution, memory, and context management (preferred).
Experience developing LLM evaluation frameworks, regression benchmarks, and observability systems to improve agent reliability and reasoning quality (preferred).
Machine Learning
NLP
Deep Learning
Information Retrieval
Reinforcement Learning
Statistics
Optimization
Forecasting
Agile
Production Systems
Design of Experiments