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Apple

Machine Learning Engineering Manager

Posted 23 days ago

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Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

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.

Description
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

Preferred 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
Experience in the following a plus: payments, finance, or financial risk

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
Experience in the following a plus: payments, finance, or financial risk

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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