Machine Learning Engineer Manager - APAC

Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of data scientists 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 for Apple's fulfilment and financial programs. You will engage with a large and talented cross-functional team as we work to build out our solutions, projects and programs.

Apple's dedication to customer privacy, the adversarial nature of trader and 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 data science methods with engineering and business process to deliver tangible business value!

This position is based in Singapore.

Lead and mentor a team of software developers and machine learning engineers
Design and maintain real-time automated decisioning systems and operations for fulfilment and 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 them technical solutions
Review the teams production code and logic for highly integrated system.
Distill and clearly communicate complex technical topics for both business and engineering stakeholders
Analyze data and tell meaningful stories to assist business partners.
Collaborate with and support the team to innovate, encouraging experimentation and growth.

Minimum Qualifications

• Graduate degree in a quantitative field or equivalent professional experience.

• Experience leading a team of machine learning engineers and software 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.