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: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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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 AI/ML Engineer: System RF Data Ecosystem joins the Smart Data Ecosystem team within the System RF group. This role focuses on building AI/ML-powered analytics to unlock insights from complex wireless manufacturing and design data. You will architect, develop, and deploy scalable internal AI solutions, including intelligent agents that automate repetitive engineering tasks and analyze high-dimensional data. Key responsibilities include integrating Large Language Models like Anthropic Claude, Mistral, and Gemini via cloud APIs or on-premise deployments. You will also build RAG pipelines, oversee LLM fine-tuning, and design multi-agent architectures with persistent state management. Required skills include Python, FastAPI, Flask, and Agent Communication Protocols. This work solves complex system optimization problems by transforming historical design intelligence into actionable engineering productivity.

Skills

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

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.
Develop and implement rigorous Gen AI evaluation systems to measure performance, safety, and accuracy.

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 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 product goals into robust technical system designs.
10+ years of professional experience in AI/ML-related projects demonstrating long-term 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).