Apple is seeking to improve the quality and privacy of its AI assistant products, including Siri, by designing and building evaluation environments and fundamental assertions to validate instrumentation at scale with a focus on user privacy.
Requirements
- Deep understanding of large scale data validation platforms with focus on privacy
- Experience building and deploying applications with Kubernetes
- Knowledge of statistics-based evaluation approaches, ML training pipelines, and techniques for enhancing the accuracy of ML systems
- Strong programming skills in Swift, with Python experience being highly valued
- Experience building dashboards and analytics solutions using tools like Tableau, Grafana, Superset, or Splunk to visualize KPIs and monitor data quality
- Thorough understanding of backend architecture, privacy-preserving data practices, and large-scale system design
- Experience in designing and building scalable ETL pipelines, high-performance data stores, and automated workflows
Responsibilities
- Designing, building, and evolving the evaluation environments and fundamental assertions to validate the instrumentation of AI assistant products at scale with a focus on user privacy
- Creating tools and frameworks for instrumentation and privacy evaluation
- Ensuring that AI products meet their privacy promises and are instrumented for trustworthy measurement
- Collaborating closely with data and product engineering teams to provide evaluation methodologies and automation frameworks within a micro-services architecture
- Building and deploying applications with Kubernetes
- Designing and building scalable ETL pipelines, high-performance data stores, and automated workflows
- Building dashboards and analytics solutions using tools like Tableau, Grafana, Superset, or Splunk to visualize KPIs and monitor data quality
Other
- 5+ years of proven experience designing, implementing, and optimizing large-scale data-driven platforms and frameworks, APIs, services, and tools
- BS/MS or equivalent experience in Computer Science, Engineering, or a related field
- Demonstrated success in collaborating cross-functionally with engineering, machine learning, and data science teams to solve sophisticated challenges
- Strong attention to detail and proven track record of delving into data, uncovering hidden patterns, and conducting comprehensive error/deviation analysis
- Apple is an equal opportunity employer that is committed to inclusion and diversity
