Sr Software Engineer, Siri User Experience Metrics and Data

We're looking for a Senior Software Engineer to help build the next generation of large-scale data systems that power high-impact decisions across Siri. In this role, you'll operate at the intersection of engineering excellence and business impact. You'll design and implement scalable, reliable systems to transform raw data into actionable insights for leadership. This is a high-visibility, high-impact position with the opportunity to influence the direction of products and strategy\\n\\nThe Siri User Experience Metrics team is at the heart of shaping how users interact with Siri every day. We use data, metrics and insights to continuously improve Siri's User Experience across Apple platforms including iOS, macOS, visionOS, tvOS and watchOS.\\n\\nOur team defines and owns the most critical user facing metrics, identifies quality issues, builds scalable reporting tools and delivers actionable insights that directly inform product decisions. We collaborate closely with product, platform and feature teams to ensure Siri not only works - but delivers exceptional User Experience. From response time to failure tracking, we make sure Siri feels fast, natural and helpful wherever users need it.\\n\\nAs a Senior Software Engineer on the Siri User Experience Metrics team, you will have significant influence and responsibility in identifying and alert on quality issues using data and metrics to shape Siri's User Experience.\\n\\nIf this sounds like you, you're someone who's laser-focused on impact - bringing sharp programming skills, strong problem-solving abilities and clear communication to the table, all driven by a passion for building exceptional products.\\n\\nYou'll have the opportunity to drive meaningful impact across all Apple platforms by collaborating closely with Engineering, Product, Testing and Quality teams. Your work will directly enhance the Siri experience for billions of users - shaping how people interact with Apple every day.

Join us in building the data backbone of Siri's regression detection system - the platform that enables engineering teams and senior leadership to see, understand, and improve product quality. In this role, you'll build large-scale data systems that power metrics observability at scale. Success in this role means not only technical excellence, but also the ability to collaborate across teams, communicate effectively and align diverse stakeholders around solving complex, high-impact challenges.\n\nYou thrive in fast-paced, dynamic environments and are comfortable navigating ambiguity to deliver meaningful, incremental impact. You bring strong problem-solving skills, operate with a high degree of autonomy and have a track record of executing effectively. With a commitment to continuous learning and attention to detail, you actively seek opportunities to innovate and share knowledge. You follow engineering best practices - including unit testing, CI/CD, documentation, monitoring, and alerting - to ensure reliable, maintainable solutions. In this role, you'll collaborate closely with stakeholders to understand metric needs, provide technical guidance, gather requirements and deliver robust data solutions and intuitive dashboards.

7 years of development experience and Bachelors or Masters degree in Computer Science or related field or 5 years development experience and PhD in Computer science or related field. \nExpert knowledge of one or more object-oriented programming languages (Java, Objective-C, C++, Scala, Swift etc) or scripting languages (Python, Ruby, Bash etc.).\nExperience working with Spark or other distributed data technologies (e.g. Hadoop, Presto, Flink, Druid) for building efficient and large scale data systems.\nExpertise in development of big data systems and ETL for product metrics and analysis of large data volumes to identify patterns, draw insights and troubleshoot issues. \nKnowledge of SQL to analyze data, derive insights and drive improvements.\nLeadership experience, including being a technical lead for complex, cross functional development projects demonstrating good technical judgement and prioritization skills.

Experience supporting the end-to-end machine learning lifecycle, including data ingestion, feature pipelines, batch inference, and model monitoring in production environments.\nHands-on experience building, scheduling, and maintaining data and ML workflows using orchestration frameworks such as Apache Airflow\nExperience working in cloud environments (AWS, Google Cloud Platform, or Azure) and integrating data pipelines with cloud-native storage and compute services