Applied AI Engineer

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $150,400–$277,600 / yr
Posted: 1 day ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $226k

This role $214k

$135k $293k

below market most similar roles pay here above market

This role pays less than 51% of similar roles. Most pay $196,975–$254,750 — the blue band above. At the midpoint, this role pays about $214k versus about $226k 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 3515 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2718 roles with salary data.

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At a glance

TL;DR · Applied AI Engineer

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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 facilitate natural language querying. Key responsibilities include designing scalable agent systems, managing orchestration, tool calling, memory, context retrieval, and intelligent routing. You will build reusable platform components, evaluation frameworks, and monitoring systems to improve observability and accuracy. The role requires proficiency in Python, software engineering fundamentals, and experience with LLM-powered applications using agentic workflows, RAG, and distributed data systems. You will solve complex business challenges by translating domain expertise into production-ready AI solutions that improve how teams access insights and make data-driven decisions.

Skills

Python LLMs Agentic AI RAG Machine Learning SQL Model Fine-tuning Inference Optimization Embeddings Statistics Observability Production Engineering

What you'll do

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.
Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field (preferred).
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 production AI agent platforms, LLM evaluation frameworks, advanced retrieval, or natural-language-to-SQL systems (preferred).