Applied AI Engineer

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.\\n\\nApple'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.\n\nWe'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.\nExperience with rapid prototyping, reproduction, and validation of research ideas.\nProven ability to translate complex research ideas into scalable, production-level AI solutions.\nDemonstrated 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.\nComfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.\nProficiency in Python (FastAPI, LangChain, or similar frameworks), context engineering, and RESTful API design.\nAbility to build relationships and collaboration opportunities within Channel Sales and with other orgs i.e AIML, SWE etc.\nCommunicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences.\nHands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows.\nProven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.).\nSolid grounding in data structures, async programming, and pipeline orchestration.\nAbility 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.\nHands-on industry experience shipping LLM-powered products or features.\nExperience with personalization, recommendation systems, or commerce intelligence.\nExperience with anomaly detection and causal inference models.\nSound 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.\nFamiliarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs. \nOther complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred.\nExperience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).