AI/ML Engineer: System RF Data Ecosystem - Jobs - Careers at Apple
- Integrate Large Language Models: Direct the integration of state-of-the-art LLMs (such as Anthropic Claude, Mistral, and Gemini) via both cloud-based APIs and secure on-premise deployments.
- Orchestrate Tool-Use and Integration: Develop safe and efficient mechanisms for agents to invoke APIs, query high-dimensional databases, and interact with custom internal engineering tools.
- Optimize Retrieval and Knowledge: Architect and maintain advanced RAG (Retrieval-Augmented Generation) pipelines and oversee LLM fine-tuning processes to align models with domain-specific engineering data.
- Design and Architect Multi-Agent Systems: Lead the development of sophisticated multi-agent architectures, specifically focusing on complex orchestration, coordination, and persistent state management.
- Scalable Deployment: Oversee the transition of AI solutions from experimental prototypes to robust, production-scale internal services that handle complex, high-volume engineering requests.
- 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.
- Proven ability to build efficient interfaces for agents to invoke APIs, query high-dimensional databases, and interact with custom toolsets.
- Proficiency in Python (Core and Async) and a strong command of FastAPI or Flask for serving high-performance AI endpoints.
- Proven success in deploying Generative AI solutions tailored to complex, high-dimensional, and domain-specific engineering data.
- Prior experience overseeing the full lifecycle of large-scale software applications deployed within an enterprise-grade production environment.
- Deep understanding of model selection, intelligent routing, and fallback strategies to ensure reliability across multiple LLM providers.
- Experience developing and implementing rigorous Gen AI evaluation systems to measure the performance, safety, and accuracy of deployed agents
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🇬🇧 English