AI/ML Engineer: System RF Data Ecosystem

Apple • Cupertino, CA

1h

About The Position

The Smart Data Ecosystem team in Apple’s System RF group builds AI/ML-powered analytics that generate insights from complex wireless manufacturing and design data. This role focuses on transforming engineering productivity and supporting hardware design through machine learning and generative AI. The engineer will connect hardware engineering workflows with AI by architecting intelligent agents that automate repetitive tasks, analyze high-dimensional data to reveal trends, and draw on historical design intelligence. These systems help engineers make critical decisions more quickly and accurately and contribute to the development of Apple products.

Requirements

• At least 7 years of experience in AI/ML-related projects.
• A proven track record of architecting and deploying production-scale generative AI solutions.
• A 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 knowledge of agent communication protocols such as MCP and A2A, and frameworks for distributed agentic workflows.
• Expert software development skills and a solid foundation in architectural design and scalable, modular systems.
• Ability to lead cross-functional architecture discussions and translate product goals into robust technical designs.

Nice To Haves

• At least 10 years of professional experience in AI/ML-related projects, with a record of innovation and technical leadership.
• Experience building efficient agent interfaces for API invocation, high-dimensional database queries, and custom toolsets.
• Proficiency in Python, including core and async programming, and strong command of FastAPI or Flask.
• Success deploying generative AI solutions for complex, high-dimensional, domain-specific engineering data.
• Experience overseeing the full lifecycle of large-scale software applications in an enterprise-grade production environment.
• Deep understanding of model selection, intelligent routing, and fallback strategies across multiple LLM providers.
• Experience developing rigorous generative AI evaluation systems for measuring agent performance, safety, and accuracy.

Responsibilities

• Architect, develop, and deploy scalable AI solutions for internal use.
• Design intelligent agents to automate repetitive engineering tasks.
• Analyze high-dimensional data to surface trends and insights.
• Enable access to historical design intelligence to support engineering decisions.
• Translate product goals into robust technical system designs.
• Lead cross-functional architecture discussions.
• Build interfaces that allow agents to invoke APIs, query high-dimensional databases, and interact with custom toolsets.
• Develop and deploy generative AI solutions for domain-specific engineering data.
• Oversee the lifecycle of large-scale software applications in an enterprise production environment.
• Develop evaluation systems to measure deployed agents’ performance, safety, and accuracy.

What This Job Offers

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