Applied AI Engineer

Apple • Cupertino, CA

1d

About The Position

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. Work at the intersection of applied AI and business operations —translating frontier engineering research into practical, scalable features for AI products.

Requirements

• 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.

Nice To Haves

• 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).

Responsibilities

• Design and develop agentic AI systems that reason, plan, and act across tools and modalities.
• Translate research into production-ready tools by partnering with platform engineers to productionize your methods into SDKs and APIs.
• Prototype and evaluate novel approaches, combining research exploration with hands-on engineering to translate innovations from concept to production.
• Build scalable pipelines for multi-modal agent input, memory, and semantic routing.
• Work closely with partner teams to build, iterate, and adapt innovative solutions in a dynamic, product-focused environment.
• Partner closely with data science, engineering, and sales ops to embed context-aware intelligence in decision-making tools.
• Lead technical decision-making on infrastructure components, embedding safety mechanisms (e.g., autonomy sliders, grounding checks, model monitoring).
• Collaborate closely with business teams to incorporate AI into their weekly cadences.

What This Job Offers

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