Summary

Posted: Jan 8, 2021

Role Number:200215050

At Apple, great ideas have a way of becoming great products and services. If you are a self-motivated and high-energy person who is...Summary

Summary

Posted: Jan 8, 2021

Role Number:200215050

At Apple, great ideas have a way of becoming great products and services. If you are a self-motivated and high-energy person who is not afraid of challenges, we are looking for you!

Apple is seeking an ML Advanced Research and Applications Manager to join AMP Data Science & Analytics, covering App Store, Apple Music, Apple TV, Apple Podcasts, Apple Fitness+, etc.

AMP Data Science & Analytics collaborates with executives and various partners across the business, product, design, and engineering. Our mission is to deliver insights to drive decisions that improve the customer experience, drive growth, and uncover new business opportunities.

Key Qualifications

• Experience in ML time series anomaly detection, forecasting, causal inference, or others
• Contributions to ML communities such as NeurIPS, JMLR, ICML, etc.
• Strong proficiency in Python and SQL
• 2+ years of experience in managing an ML or software engineering team
• Hands-on experience in designing and developing ML applications
• Team player with excellent communication and collaboration skills
• Industry experience in agile development and DevOps

Lead a team of multi-discipline engineers (ML engineers, ML researchers, software engineers, etc.)

Collaborate with data science teams and applied ML teams to understand user needs

Work closely with product management to define strategy and roadmap

Conduct cutting-edge machine learning research to identify innovative approaches to time series anomaly detection, forecasting, causal inference, and more

Translate research outcomes into the design and development of ML applications for data scientists and applied ML engineers

Collaborate with engineering partners (development, platform, SRE, etc.) for the delivery of production-scale ML applications

Be in constant dialog with data science teams and applied ML teams to prototype and launch ML applications, understand the impact, and iterate on features and capabilities

Education & Experience

Minimum of a Bachelors degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, Economics or related field. Ideally, Masters or Ph.D. in a related field.

Additional Requirements