AIML Architect, Retail and Marcom Engineering

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world Join Apples Information Systems and Technology (ISu0026T) organization. ISu0026T is the engine behind everything Apple does for customers and for the people who build for them. Its Apples central nervous system. Supporting 2.5 billion active Apple devices processing billions of secure transactions and keeping the technology that defines modern life running flawlessly ISu0026T makes the impossible feel effortless. Do you love building solutions to handle global complexity and immense scale Imagine what you could do and Marcom Engineering an ISu0026T team builds and operates the systems and experiences that connect Apples products with its customers. The team owns the technology behind both Apples online and physical stores and drives the interactive marketing experiences and tools that keep creative operations moving. Together those functions deliver the technology behind every product story Apple tells and every purchase a customer makes.

Were seeking a visionary AI/ML Architect to shape the technical strategy behind Apples globally-led creative marketing team. You will define the architecture for cutting-edge AI/ML solutions directly influencing how millions of Apple customers experience our brand. Lead the design of systems involving GenAI LLMs Graph RAG and multi-modal models architecting intelligent agentic workflows that redefine whats possible. If youre ready to set the technical direction for AI/ML at a global scale this is your an AI/ML Architect youll define the technical vision and architecture for intelligent experiences owning the end-to-end system design across the machine learning lifecycle. Partnering with business and engineering stakeholders youll define AI/ML architecture strategy evaluate build vs. buy tradeoffs and establish design patterns that leverage LLM technologies to unlock new insights at scale. nnYour expertise will guide multiple teams on architectural best practices for LLM and GenAI usage ensuring platform scalability reliability and long-term maintainability. Youll architect complex AIOps systems establishing frameworks for clustering classification anomaly detection and capacity prediction to optimize our systems.

Architectural Ownership: Define and own the end-to-end architecture for AI/ML systems establishing standards design patterns and best practices across System Architecture at Scale: Deep expertise architecting end-to-end GenAI pipelines (model selection fine-tuning RAG guardrails) aggressively optimizing for latency hallucination rates and token costs at enterprise scalenPlatform u0026 Systems Design: Architect scalable resilient Conversational AI platforms and virtual assistant frameworks that serve as the foundation for multiple product Strategy u0026 Roadmap: Partner with business and engineering leadership to define the AI/ML architecture roadmap identify strategic opportunities and guide the adoption of LLM-driven analytic solutions across the Leadership: Mentor engineering teams on architectural decisions review system designs and ensure alignment with enterprise-wide technical standards.

10 years of experience in software engineering or AI/ML including 3-4 years in an architect or technical leadership role designing enterprise-scale AI/ML of core AI/ML concepts (supervised and unsupervised learning deep learning anomaly detection) and the ability to translate them into scalable system delivering production generative AI solutions with working knowledge of LLM architectures fine-tuning techniques and designing and optimizing prompt strategies at scale with measurable gains in LLM accuracy latency or architecting multi-agent systems using orchestration frameworks (e.g. LangChain LangGraph AutoGen) with a focus on rapid experimentation and continuous prompt and model designing integration architectures that connect AI and bot systems with backend systems databases and APIs to deliver robust end-to-end record of designing building and scaling AI/ML platforms and services that handle high data and traffic volumes in enterprise defining technical standards conducting architecture reviews and driving consistency across distributed engineering and analytical skills with the ability to diagnose and resolve complex issues in distributed in Engineering Computer Science or a related field or equivalent experience.

MS or PhD in Engineering Computer Science or a related architecting solutions with multi-modal models and Graph RAG establishing RAG benchmarking frameworks and evaluation with model optimization techniques such as distillation quantization and parameter-efficient fine-tuning and a record of quickly evaluating and prototyping emerging approaches (e.g. fine-tuning vs. RAG).nExperience architecting conversational AI platforms at scale including intent recognition dialogue management and natural language of DevOps practices including CI/CD pipelines infrastructure as code (e.g. Terraform) containerization (Docker) and Git-based workflows for automated build test and deployment of ML of SRE principles including defining SLIs/SLOs monitoring and alerting incident response root cause analysis and building for reliability in production architecting AIOps solutions including clustering classification anomaly detection and capacity with LLMOps including evaluation observability guardrails and cost and token with responsible AI practices including privacy brand safety and in marketing creative content or personalization independent mindset with strong leadership instincts and the ability to thrive in a fast-paced dynamic environment.n