Machine Learning Engineering Manager

Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of machine learning engineers that craft, implement, and operate analytical solutions with direct and measurable impact to Apple and its customers.

You will build and lead a team of SDS machine learning engineers, who employ machine learning, statistical analysis techniques, and system design to build end-to-end solutions across Apple's business operations.

You will engage with a large and talented cross-functional team as we work to build out our data-driven programs. Apple's dedication to customer privacy, the adversarial nature of risk, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, you will push the limits of integrating existing machine learning methods with engineering and business process to deliver tangible value.

Lead and mentor a team of software developers and machine learning engineers
Design and maintain real-time automated decisioning systems and operations for financial products
Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions
Engage with business partners and understand their unique requirements and design technical solutions
Review the team's production code and logic for highly integrated systems
Distill and clearly communicate complex technical topics for both business and engineering stakeholders
Analyze data and tell meaningful stories to assist business partners

Minimum Qualifications

• Experience leading a team of machine learning engineers

• Practical experience training, deploying, and maintaining decisioning algorithms

• Familiarity with distributed databases, data warehousing, and SQL

• Ability to implement custom real-time or batch machine learning applications with their appropriate data pipelines

• Ability to comprehend and debug complex system integrations spanning toolchains and teams

• Ability to extract meaningful business insights from data and identify the stories behind the patterns

• Ability to think at a systems level to anticipate technical, business, and customer impact

• Clear communication and presentation skills

• Excellent problem solving skills, business acumen, and solution design mentality

• Experience writing, reviewing, and deploying production software

• Graduate degree in a quantitative field or equivalent professional experience