Machine Learning Engineering Manager - Online Retail Analytics

Austin, Texas, United States
Machine Learning and AI


Weekly Hours: 40
Role Number:200193212
Apple's Online Retail Analytics 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 that have direct and measurable impact to Apple and its customers. You will build and lead a team of machine learning engineers who design, build and deploy predictive modeling on production systems to drive increased sales and improved customer experience for our online customers. Apple's dedication to customer privacy 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 existing methods while delivering tangible business value.

Key Qualifications

  • Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, recommender systems, reinforcement learning and anomaly detection
  • Familiarity with database modeling and data warehousing principles
  • Familiarity with Big Data tools like Spark, Hive etc.
  • Strong programming skills in Java, Python, or similar language
  • Experience developing enterprise production software
  • Ability to comprehend and debug complex systems integrations spanning toolchains and teams
  • Ability to extract meaningful business insights from data and identify the stories behind the patterns
  • Creativity to engineer novel features and signals, and to push beyond current tools and approaches
  • 2+ years experience in hiring & leading team of machine learning engineers
  • Ability to coach data scientists and a drive to invest in team’s success
  • Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways


• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions • Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem • Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions • Ensure operational and business metric health by monitoring production decision points • Investigate buying trends, identify behavior patterns, and respond with agile logic changes • Communicate results to business partners and executives • Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team • Coach data scientists and machine learning engineers for their individual career development • Deliver timely, constructive feedback to help team members recognize their needs and their progress • Drive the collaborative and supportive culture on your team, and partner with peers to share best practices across the larger organization

Education & Experience

• Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.

Additional Requirements