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Sr Software Engineer, Siri User Experience Metrics and Data

Apple
Posted 9 days ago, valid for 5 days
Location

Cupertino, CA 95015, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Join the Siri organization as a Senior Software Engineer to help redefine a personal and integrated AI assistant, impacting users across multiple Apple platforms.
  • The role requires a minimum of 7 years of development experience or 5 years with a PhD, along with expertise in object-oriented or scripting languages and distributed data technologies.
  • You will design scalable data systems for metrics observability, collaborating with various teams to enhance Siri's user experience through actionable insights.
  • The position emphasizes technical excellence, problem-solving, and effective communication, with a strong focus on building reliable and maintainable solutions.
  • The salary for this position is competitive, reflecting the high-impact nature of the work and the level of experience required.
Join the team redefining what a deeply personal and integrated assistant can be. As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS. This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs. 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 The 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. Our 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. As 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. If 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. You'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.

Description


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. You 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.

Minimum Qualifications


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. Expert knowledge of one or more object-oriented programming languages (Java, Objective-C, C++, Scala, Swift etc) or scripting languages (Python, Ruby, Bash etc.). Experience working with Spark or other distributed data technologies (e.g. Hadoop, Presto, Flink, Druid) for building efficient and large scale data systems. Expertise 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. Knowledge of SQL to analyze data, derive insights and drive improvements. Leadership experience, including being a technical lead for complex, cross functional development projects demonstrating good technical judgement and prioritization skills.

Preferred Qualifications


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



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