A
Applied AI Engineer
Apple
- Location
- Onsite (Cupertino, California)
- Employment
- Full-time
- Level
- Senior Level
Posted 3 weeks ago
About the Role
Apple's US Decision Intelligence team is seeking an Applied AI Engineer to craft and implement AI solutions that directly impact Apple Sales operations. This role focuses on leveraging LLMs and agentic workflows to enhance business intelligence and drive innovation in AI-driven capabilities.
Skills
Applied AI
Machine Learning
Large Language Models
Agentic Workflows
Python
FastAPI
LangChain
LlamaIndex
Vector Databases
RESTful API Design
Statistical Modeling
Async Programming
Pipeline Orchestration
Context Engineering
Data Structures
Distributed Systems Architecture
Full job details
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Apple’s Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers. We’re looking for a hands-on Applied AI Engineer with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems. You will strengthen our team’s capabilities in machine learning, and foundational AI development. This role will drive innovation in building scalable ML and AI solutions that enhance our internal AI products intelligence, improve automation, and expand our AI-driven capabilities across business domains. The ideal candidate combines deep technical expertise in machine learning, statistical modeling, and AI framework development with strong problem-solving and interpersonal skills, ensuring effective collaboration and measurable impact in a fast-paced environment.
PhD in Computer Science, Statistics, Mathematics, AI, or a related quantitative field with 3+ years of experience in applied AI, machine learning, or statistical modeling.; or MS with 6+ years of experience in applied AI, machine learning, or statistical modeling. Experience with rapid prototyping, reproduction, and validation of research ideas. Proven ability to translate complex research ideas into scalable, production-level AI solutions. Demonstrated ability to work across the research-to-production spectrum: you have taken experimental or prototype code and made it robust, scalable, and usable by others. Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales. Proficiency in Python (FastAPI, LangChain, or similar frameworks), context engineering, and RESTful API design. Ability to build relationships and collaboration opportunities within Channel Sales and with other orgs i.e AIML, SWE etc. Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences. Hands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows. Proven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.). Solid grounding in data structures, async programming, and pipeline orchestration. Ability to balance competing priorities, long-term projects, and ad hoc requirements in a fast-paced, dynamic, constantly evolving business environment.
Strong experience articulating and translating business questions into AI solutions. Hands-on industry experience shipping LLM-powered products or features. Experience with personalization, recommendation systems, or commerce intelligence. Experience with anomaly detection and causal inference models. Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership. Familiarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs. Other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred. Experience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).
Description
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers. We’re looking for a hands-on Applied AI Engineer with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems. You will strengthen our team’s capabilities in machine learning, and foundational AI development. This role will drive innovation in building scalable ML and AI solutions that enhance our internal AI products intelligence, improve automation, and expand our AI-driven capabilities across business domains. The ideal candidate combines deep technical expertise in machine learning, statistical modeling, and AI framework development with strong problem-solving and interpersonal skills, ensuring effective collaboration and measurable impact in a fast-paced environment.
Minimum Qualifications
PhD in Computer Science, Statistics, Mathematics, AI, or a related quantitative field with 3+ years of experience in applied AI, machine learning, or statistical modeling.; or MS with 6+ years of experience in applied AI, machine learning, or statistical modeling. Experience with rapid prototyping, reproduction, and validation of research ideas. Proven ability to translate complex research ideas into scalable, production-level AI solutions. Demonstrated ability to work across the research-to-production spectrum: you have taken experimental or prototype code and made it robust, scalable, and usable by others. Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales. Proficiency in Python (FastAPI, LangChain, or similar frameworks), context engineering, and RESTful API design. Ability to build relationships and collaboration opportunities within Channel Sales and with other orgs i.e AIML, SWE etc. Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences. Hands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows. Proven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.). Solid grounding in data structures, async programming, and pipeline orchestration. Ability to balance competing priorities, long-term projects, and ad hoc requirements in a fast-paced, dynamic, constantly evolving business environment.
Preferred Qualifications
Strong experience articulating and translating business questions into AI solutions. Hands-on industry experience shipping LLM-powered products or features. Experience with personalization, recommendation systems, or commerce intelligence. Experience with anomaly detection and causal inference models. Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership. Familiarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs. Other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred. Experience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).
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