AI/ML Engineer: System RF Data Ecosystem

Apple • Cupertino, CA

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About The Position

The Senior AI Development Engineer will architect, develop, and deploy scalable AI solutions for Apple’s Smart Data Ecosystem team within the System RF group. The team builds AI/ML-powered analytics that generate insights from wireless manufacturing and design data across Apple products. This role applies machine learning and generative AI to improve engineering productivity and hardware design workflows. The engineer will build intelligent agents to automate repetitive tasks, analyze high-dimensional data, surface trends, and draw on historical design intelligence to help engineers make decisions more quickly and accurately.

The role includes integrating large language models through cloud APIs and secure on-premise deployments; developing safe mechanisms for agents to use APIs, databases, and internal engineering tools; architecting retrieval-augmented generation pipelines and overseeing model fine-tuning; designing multi-agent systems; and taking AI solutions from prototypes to robust, production-scale internal services.

Requirements

• At least 7 years of experience in AI/ML-related projects, with a track record of architecting and deploying production-scale generative AI solutions.
• Master’s or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
• Expert knowledge of multi-agent system design, including orchestration, coordination, and persistent state management.
• Strong command of agent communication protocols such as MCP and A2A, and frameworks for distributed agentic workflows.
• Expert software development skills and a strong foundation in architectural design and scalable, modular systems.
• Ability to lead cross-functional architecture discussions and translate product goals into robust technical designs.
• At least 10 years of professional experience in AI/ML-related projects, with a track record of innovation and technical leadership.
• Ability to build efficient interfaces for agents to invoke APIs, query high-dimensional databases, and interact with custom toolsets.
• Proficiency in Python, including core and asynchronous programming, and strong command of FastAPI or Flask for high-performance AI endpoints.
• Success deploying generative AI solutions for complex, high-dimensional, domain-specific engineering data.
• Experience overseeing the full lifecycle of large-scale software applications in enterprise-grade production environments.
• Deep understanding of model selection, intelligent routing, and fallback strategies for reliability across multiple LLM providers.
• Experience developing and implementing rigorous generative AI evaluation systems to measure deployed agents’ performance, safety, and accuracy.

Responsibilities

• Integrate state-of-the-art large language models, including models such as Anthropic Claude, Mistral, and Gemini, through cloud APIs and secure on-premise deployments.
• Develop safe and efficient mechanisms for agents to invoke APIs, query high-dimensional databases, and interact with internal engineering tools.
• Architect and maintain retrieval-augmented generation (RAG) pipelines and oversee LLM fine-tuning to align models with domain-specific engineering data.
• Lead development of multi-agent architectures, including orchestration, coordination, and persistent state management.
• Oversee the transition of AI solutions from experimental prototypes to robust, production-scale internal services.
• Lead cross-functional architecture discussions and translate product goals into technical system designs.
• Develop and implement generative AI evaluation systems to measure agent performance, safety, and accuracy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior