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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AIML - Sr Data Engineer, DMLI - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Airflow, Data Analysis, Automated Storage and Retrieval Systems, BigQuery, Cloud Engineering, Code Review, Encodings, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Dataspaces, Data Systems, Software Debugging, Distributed Systems, Data Flow Control, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Query Optimization, Cloudera, Software Engineering, Data Streaming, Google Cloud, Feature Engineering, Large Language Models, Apache Spark, Generative AI, Event Driven Architecture, Information Technology, Data Lineage, Data Management, Machine Learning Operations, Artificial Intelligence Markup Language (AIML), Software Version Control, Data Pipelines, Apache Beam - **Published:** July 30, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3336268367&tx=FR9794FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). * Strong software engineering foundation with 5+ years of experience in data engineering, backend engineering, or distributed systems. * Strong hands-on experience designing and building large-scale batch and streaming data pipelines using Python and distributed systems. * Expertise in ETL/ELT development, event-driven architectures, and working with high-volume datasets using technologies such as Pub/Sub, Dataflow (Apache Beam), and Spark-based processing (Dataproc or equivalent). * Deep expertise in the Google Cloud Platform data ecosystem, including BigQuery, Dataflow, Pub/Sub, and Composer (Airflow). Proven ability to design, optimize, and operate scalable data platforms, with strong experience in BigQuery performance tuning, cost optimization, data modeling, partitioning, clustering, and query optimization at scale. * Proficient in Python, version control, CI/CD practices, testing, and code reviews., * 7+ years of experience in data engineering or large-scale distributed systems. * Experience designing end-to-end data platforms or data mesh architectures. * Strong understanding of data governance, data lineage, and metadata management frameworks. * Experience supporting ML pipelines and MLOps workflows, including feature engineering and training data generation. * Experience building systems with strong reliability, observability, and SLAs (monitoring, alerting, debugging distributed pipelines). * Familiarity with Generative AI / LLM-based systems, including: LLM-powered data workflows, Agentic pipelines, Embedding/vector-based retrieval systems. * Experience influencing architecture decisions across teams and driving technical direction. * Experience collaborating in cross-functional, fast-paced tech environments or cloud-native organizations with a focus on building reliable, maintainable, and production-grade data systems. ## Description Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide!, The AI and Machine Learning team is looking for Senior Data Engineer to build world-class data infrastructure and solutions that are used by data scientists, ML engineers and researchers to power Apple Foundation Model lifecycle., We are looking for a skilled Senior Data Engineer to join our engineering team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data platforms, and data integration solutions that enable reliable analytics, machine learning, and business intelligence capabilities across the organization. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)