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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AIML - Sr Software Data Engineer, Evaluation - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Expert - **Salary:** $181,100.0 - $318,400.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Airflow, Data Analysis, Automation of Tests, Batch Processing, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Data Structures, Distributed Computing Environment, Distributed Data Store, Fault Tolerance, Python (Programming Language), Machine Learning, Scala (Programming Language), Software Engineering, SQL Databases, Data Processing, Feature Engineering, Apache Spark, Siri, Information Technology, Apache Flink, Apache Kafka, Artificial Intelligence Markup Language (AIML), Software Version Control, Data Pipelines, Programming Languages - **Published:** May 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c71a74ae13ca0458 ## About the Role Do you have experience in Software engineering?, Do you have a Bachelor's degree?, Strong in algorithms, data structures, data modeling, and SQL, with experience working on large-scale, complex, and high-dimensional datasets. Experience with machine learning algorithms or pipelines, particularly in the context of data engineering. Experience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus. Familiarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing). Proven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices. Comfortable working independently in a fast-paced, ambiguous environment. Excellent communication and problem-solving skills. Minimum Qualifications 7+ years of experience designing, building, and maintaining distributed data processing systems at scale. 5+ years of hands-on experience with stream and/or batch processing technologies such as Flink, Spark, Kafka, Airflow, Iceberg, and Trino. 2-3 years of experience in full-stack development Proficient in at least one modern programming language (e.g., Java, Scala, and Python). MS or BS in Computer Science, Engineering, Math, Statistics, or a related field, or equivalent practical experience in data engineering. ## Description Are you excited about using data to shape the experience of products used by hundreds of millions of people around the world? The Evaluation Data Engineering team, part of Apple's SWE organization, builds the scalable and reliable data platform that powers Siri, Search, and Machine Learning across Apple. We're looking for collaborative and mission-driven software engineers who care deeply about data quality, user impact, and building at scale. If you're passionate about tackling complex data challenges, eager to work with petabytes of data, and inspired by Apple's commitment to privacy and innovation, we'd love to hear from you., In this role, you'll work cross-functionally across product and data science teams to build large-scale stream and batch processing data pipelines that power Analytics, Experimentation, and Machine Learning. You will design a unified and groundbreaking data processing framework using Flink, and/or Spark. Your work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the framework's capabilities to new user scenarios and groundbreaking machine learning applications. You will collaborate closely with Siri, Search, and other teams to design solutions that transform raw data into datasets that drive innovation. You'll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights. ## Related Videos - [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) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Lessons from Steve Jobs - Learnings from the Past for the Future](https://www.wearedevelopers.com/videos/1021-lessons-from-steve-jobs-learnings-from-the-past-for-the-future) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) ## 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) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)