Applied AI Engineer

Apple • Cupertino, CA

14h

About The Position

Join Apple's engineering team building AI systems and infrastructure that improve how engineers work and help move Apple's algorithms programs into the AI era. The role focuses on AI-native platforms and data systems that connect AI capabilities with organizational context, data, and tools, making them useful to engineers developing next-generation sensing technologies. Some solutions will support internal workflows, while others may develop into broader products and tools.

You will work with machine learning scientists, algorithm engineers, hardware teams, designers, and human factors researchers. As part of a small, high-impact group, you will influence the architecture and direction of its platforms. The work spans software, hardware, and design, and aims to help teams make better decisions and ship devices faster. The ideal candidate has shipped AI-powered tools used by real users, such as systems that reason over internal documents, orchestrate multi-step tool calls, or turn unstructured data into searchable knowledge.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• At least 3 years of relevant industry experience.
• Proficiency in Python and at least one of Swift, TypeScript, or another systems-level language.
• Experience designing and building backend services, data pipelines, or platform infrastructure.
• Hands-on experience building with modern AI or agent frameworks.
• Strong software architecture and API design skills, with a systems-oriented approach.
• Experience building retrieval pipelines, such as RAG, embeddings, or vector search, or other knowledge retrieval systems.
• Strong communication skills and ability to work effectively across disciplines.
• Experience evaluating and iterating on AI system outputs, including building evaluation pipelines and measuring quality.
• Strong problem-solving skills and a bias toward shipping.

Nice To Haves

• Master's or PhD in Computer Science, Software Engineering, Data Engineering, or a related field.
• Experience building macOS or iOS client applications.
• Background in workflow orchestration, experiment tracking, or reproducibility tooling.
• Experience designing data models, storage layers, or integration APIs for complex domains.
• Experience integrating LLMs with external tools and APIs using tool-use patterns, MCP, or function calling, or building custom integrations between LLMs and external systems.
• Familiarity with access-controlled or policy-aware data systems.
• Experience with vector databases or embedding pipelines such as Pinecone, Chroma, or pgvector.
• Track record building developer tools, CLIs, or internal platforms used daily by engineers.
• Experience with cloud AI services such as AWS Bedrock, Azure OpenAI, or Google Vertex AI, or self-hosted model serving.
• Contributions to open-source projects in AI/ML infrastructure.
• Comfort navigating large, established codebases and shipping iteratively within them.

Responsibilities

• Design and build AI-native platforms and data systems that accelerate engineering workflows and device development.
• Connect AI systems with organizational context, data, and tools so they can support engineers effectively.
• Develop backend services, data pipelines, and platform infrastructure.
• Build retrieval and knowledge systems, including retrieval-augmented generation, embeddings, or vector search.
• Evaluate AI system outputs, measure quality, and iterate using evaluation pipelines and feedback loops.
• Collaborate with machine learning scientists, algorithm engineers, hardware teams, designers, and human factors researchers.
• Contribute to platform architecture and help shape the direction of the group's work.

What This Job Offers

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