Siri - ML Engineering Manager, Machine Learning Systems

Seattle, Washington, United States
Machine Learning and AI


Weekly Hours: 40
Role Number:200008956
Do you want to play a part in ensuring the quality of groundbreaking technology for large scale systems, natural language, big data, and artificial intelligence? Do you want to improve the user experience of Siri and work with the people who built the intelligent assistant that helps millions of people get things done? Join the Siri Quality Engineering (QE) team at Apple! As the ML QE Manager, you will play a critical role in reinventing ML systems evaluation for Siri. You will be leveraging new approaches to validate integration of machine-learned components and evaluate the effects of training data, dependencies between components, models and non-ML code. You will also be a critical engineering partner working alongside modeling teams to drive global vs local optimization, to warrant against regressions for critical use cases, and to establish a centralized view of what quality should mean for Siri users.

Key Qualifications

  • 10+ years of professional experience or research in a related field
  • 5+ years of management experience
  • Experience with testing machine learning systems and neural networks
  • In-depth knowledge of statistics-based testing methodologies
  • Understanding of ML training pipelines and accuracy improvements of ML systems
  • Ability to develop a long term vision and execute strategies at scale
  • Programming in Java, Python, or other OO language
  • Strong verbal and written communication and organizational skills and ability to multi-task several projects
  • Self-motivated and dedicated with proven creative and critical thinking capabilities
  • Thrives on working in a fast-paced environment with rapidly changing priorities
  • Experience working in large cross-functional teams a big plus


The Siri ML QE team is searching for a talented ML Engineering Manager to create new approaches for evaluating ML based systems. This role will focus on creating an ML evaluation strategy that can adapt to Siri's evolving architecture and features. The ML QE team leads development of advanced evaluation methodologies and experimentation, to ensure that every release delivers an improved user experience. As Siri is becoming increasingly complex, it is critical to ensure that the evaluation methodology accounts for impact of the downstream ML model dependencies, impact of frameworks, and of non-ML code in assessing the final response returned by the system. In addition, the complexity of utilizing user context in ML decision making, while not having access to user data due to privacy, presents an exciting challenge for testing the final output. This role will collaborate daily with Apple ML teams, analyze results, and reach consensus as we assess the impact of changes and new features, and overall readiness for each release. This is a fast-paced role with high visibility, impact, and influence in building one the most advanced AI systems in the industry.

Education & Experience

MS/PhD in Computer Science, Machine Learning or related field

Additional Requirements