Applied AI Engineer

Apple • Cupertino, CA

1d

About The Position

Join Apple’s engineering team building AI infrastructure and tools that help engineers work more effectively and support the development of next-generation sensing technologies. The role focuses on connecting AI systems with organizational context, data, and tools, and delivering capabilities through platforms used by engineers. Some work will support internal workflows, while some may develop into products and tools used more broadly.

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 help shape the architecture and direction of AI-native platforms and data systems that improve how teams explore, analyze, and act on complex program data. The tools and infrastructure will support algorithms and features across Apple products, including iPhone, Apple Watch, and iPad.

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 Ph.D. 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 of building developer tools, CLIs, or internal platforms that engineers rely on daily.
• 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.

Responsibilities

• Build AI-powered platforms that change how engineers explore, analyze, and act on complex program data.
• Design data infrastructure that combines diverse knowledge sources and provides relevant context to AI systems and engineers with appropriate access controls.
• Create reproducible analysis workflows with provenance tracking so AI-generated insights can be trusted, iterated on, and shared across disciplines.
• Develop agentic pipelines for multi-step research and analysis while allowing engineers to steer and validate the work.
• Build infrastructure for continuous automated intelligence, including CI-integrated analysis and background monitoring.
• Design collaboration systems that help software, hardware, design, and human factors teams accumulate and use shared institutional knowledge.
• Partner with algorithm teams developing features for Apple products to understand their data challenges and deliver tooling that increases in value over time.

What This Job Offers

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