AI/ML Architect, Retail and Marcom Engineering

Apple • Sunnyvale, CA

1d

About The Position

Apple’s Information Systems and Technology (IS&T) organization supports Apple’s devices, transactions, and internal technology systems. Within IS&T, Retail and Marcom Engineering builds and operates systems and experiences for Apple’s online and physical stores, as well as interactive marketing experiences and tools for creative operations.

The AI/ML Architect will shape technical strategy for Apple’s globally led creative marketing team and define architecture for AI/ML solutions that influence customer experiences. The role owns end-to-end system design across the machine learning lifecycle, partners with business and engineering stakeholders on architecture strategy and build-versus-buy decisions, and establishes design patterns for LLM technologies. It also guides teams on LLM and GenAI architectural best practices and plans for scalable, reliable, maintainable platforms. The architect will design GenAI and AIOps systems, conversational AI platforms, and agentic workflows, while setting technical direction and mentoring engineering teams.

Requirements

• At least 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 systems.
• Understanding of core AI/ML concepts, including supervised and unsupervised learning, deep learning, and anomaly detection, and ability to translate them into scalable system architectures.
• Experience delivering production generative AI solutions, with working knowledge of LLM architectures, fine-tuning techniques, and RAG.
• Experience designing and optimizing prompt strategies at scale, with measurable improvements in LLM accuracy, latency, or cost efficiency.
• Experience architecting multi-agent systems using orchestration frameworks such as LangChain, LangGraph, or AutoGen, with focus on experimentation and continuous prompt and model iteration.
• Experience designing integration architectures connecting AI and bot systems with backend systems, databases, and APIs.
• Track record designing, building, and scaling AI/ML platforms and services that handle high data and traffic volumes in enterprise environments.
• Experience defining technical standards, conducting architecture reviews, and driving consistency across distributed engineering teams.
• Troubleshooting and analytical skills, including diagnosing and resolving complex issues in distributed environments.
• Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent experience.

Nice To Haves

• Master’s or PhD in Engineering, Computer Science, or a related field.
• Experience architecting solutions with multimodal models and Graph RAG pipelines.
• Experience establishing RAG benchmarking frameworks and evaluation methodologies.
• Experience with model optimization techniques such as distillation, quantization, and parameter-efficient fine-tuning, and quickly evaluating and prototyping emerging approaches such as fine-tuning versus RAG.
• Experience architecting conversational AI platforms at scale, including intent recognition, dialogue management, and natural language generation.
• Knowledge of DevOps practices, including CI/CD pipelines, infrastructure as code such as Terraform, containerization such as Docker, and Git-based workflows for automated build, test, and deployment of ML services.
• Knowledge of SRE principles, including defining SLIs/SLOs, monitoring and alerting, incident response, root cause analysis, and production reliability.
• Experience architecting AIOps solutions, including clustering, classification, anomaly detection, and capacity prediction.
• Experience with LLMOps, including evaluation, observability, guardrails, and cost and token optimization.
• Familiarity with responsible AI practices, including privacy, brand safety, and governance.
• Background in marketing, creative, content, or personalization technology.
• Strategic and independent mindset, strong leadership instincts, and ability to thrive in a fast-paced, dynamic environment.

Responsibilities

• Define and own end-to-end architecture for AI/ML systems, including standards, design patterns, and best practices across teams.
• Architect end-to-end GenAI pipelines, including model selection, fine-tuning, retrieval-augmented generation (RAG), and guardrails; optimize latency, hallucination rates, and token costs at enterprise scale.
• Design scalable, resilient conversational AI platforms and virtual assistant frameworks for multiple product experiences.
• Partner with business and engineering leadership to establish the AI/ML architecture roadmap, identify strategic opportunities, and guide adoption of LLM-driven analytics.
• Mentor engineering teams on architectural decisions, review system designs, and ensure alignment with enterprise technical standards.
• Architect AIOps systems and frameworks for clustering, classification, anomaly detection, and capacity prediction.
• Evaluate build-versus-buy tradeoffs and establish design patterns that use LLM technologies to unlock insights at scale.

What This Job Offers

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