AI/ML Engineer, System RF Data Ecosystem

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 48 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $197k

This role $255k

$129k $346k

below market most similar roles pay here above market

This role pays more than 96% of similar roles. Most pay $162,000–$231,187 — the blue band above. At the midpoint, this role pays about $255k versus about $197k for comparable roles.

Based on 240 similar postings.

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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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · AI/ML Engineer, System RF Data Ecosystem

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The Senior AI Development Engineer joins the Smart Data Ecosystem team within the System RF group to architect and deploy scalable AI solutions. This role focuses on transforming engineering productivity by building intelligent agents and generative AI tools that analyze high-dimensional wireless manufacturing and design data. You will integrate Large Language Models like Claude, Mistral, and Gemini via cloud APIs and on-premise deployments while maintaining RAG pipelines and fine-tuning models for domain-specific engineering data. Key responsibilities include designing multi-agent architectures with persistent state management and building interfaces for querying high-dimensional databases. You will utilize Python, FastAPI, and Flask to create production-scale internal services. This work solves complex system optimization problems by unlocking historical design intelligence to influence the performance of flagship hardware products.

Skills

Generative AI LLMs RAG Multi-Agent Systems Python FastAPI Flask MCP A2A Fine-tuning High-Dimensional Databases

What you'll do

Integrate state-of-the-art LLMs via cloud-based APIs and secure on-premise deployments.
Develop mechanisms for agents to invoke APIs, query high-dimensional databases, and interact with internal tools.
Architect and maintain advanced RAG pipelines and oversee LLM fine-tuning for domain-specific engineering data.
Lead the development of multi-agent architectures focusing on orchestration, coordination, and persistent state management.
Transition AI solutions from experimental prototypes to robust, production-scale internal services.
Implement rigorous Gen AI evaluation systems to measure performance, safety, and accuracy of deployed agents.

What we're looking for

7+ years of experience in AI/ML-related projects, with a proven track record of architecting and deploying production-scale Generative AI solutions.
Masters or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
Expert-level knowledge of multi-agent system design, including sophisticated orchestration, coordination, and persistent state management.
Strong command of Agent Communication Protocols (e.g., MCP, A2A) and frameworks for designing distributed agentic workflows.
Expert-level software development skills with a solid foundation in architectural design principles and the creation of scalable, modular systems.
Proven ability to lead cross-functional architecture discussions and translate ambitious product goals into robust technical system designs.
10+ years of professional experience in AI/ML-related projects, demonstrating a long-term track record of innovation and technical leadership (preferred).
Proficiency in Python (Core and Async) and a strong command of FastAPI or Flask for serving high-performance AI endpoints (preferred).