AI Data & Infrastructure Engineer - Jobs - Careers at Apple
- Create robust, scalable architectures for systems that handle data orchestration for AI features
- Design, build, and maintain scalable AI data platforms, services, and APIs that support and enable Agentic AI workflow development & automation.
- Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, vector database integrations, and metadata services for enterprise AI applications.
- Be able to quickly build an idea so you and the team can work with hands-on products. Then iterate on the best of those prototypes.
- Build and integrate tools that help make complex AI systems observable, understandable and debuggable
- Strong understanding of distributed systems, parallel computing, and performance optimization
- Collaborate with AI/ML engineers, software engineers, product teams, and domain experts to define AI data requirements and deliver production-ready data solutions.
- Optimize platform scalability, reliability, performance, security, and cost across cloud-native environments and Agentic systems.
- Clearly communicate complex technical problems and collaborate with partners to develop solutions
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
- 8+ Experience designing and building scalable data platforms and distributed systems.
- Strong programming skills in Python and SQL, with proficiency in Java or Scala preferred.
- Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines.
- Experience building scalable batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray, with proficiency in Pandas and modern data lake/lakehouse architectures (e.g., Iceberg, Delta Lake).
- Experience using modern development tools, including AI-assisted coding tools, while applying sound engineering judgment to review, validate, and improve generated code.
- Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI.
- Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code.
- Demonstrated ability to understand complex user workflows, translate them into practical technical solutions, and collaborate across teams to deliver measurable outcomes.
- Excellent communication and collaboration skills, with the ability to translate technical concepts into clear, business focused insights.
- Experience with or a strong understanding of Generative AI, LLMs, Agentic Systems, or RAG (Retrieval-Augmented Generation) workflows.
- Experience integrating LLMs into existing systems
- Experience with API design, both for other engineers to use, but also for AI systems.
- Experience working with manufacturing, operational, IoT, or industrial data platforms.
- Demonstrated ability to lead technical initiatives and mentor engineers.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
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Apple accepts applications to this posting on an ongoing basis.
Required Skills
Required Languages
🇬🇧 English