Applied Science Manager, Personalization & Discovery

Amazon Inc.; Asti; On-site; EUR 164,000 - 255,000; Full time

Benefits offered by this job

Health insurance

RSUs

Sign-on payments

401(k) matching

Job summary

Amazon.com Services LLC is seeking an Applied Science Manager for Prime Video Personalization & Discovery. You will lead a science team and partner with engineers, product managers, and business partners to deliver state-of-the-art personalized experiences for Prime Video across devices.

You will shape the product, roadmap, and technology choices, while hiring and growing the team, impacting millions of customers globally with personalized content recommendations.

Qualifications

• PhD or Master’s degree with extensive applied research experience.
• 3+ years in management of scientists or ML engineers.
• 4+ years of applied research experience in ML.
• 3+ years building ML models for business use cases.
• Knowledge of ML, NLP, IR and analytics; strong programming skills.

Responsibilities

• Lead development of AI solutions for Prime Video personalization and recommendations.
• Collaborate with engineers and product managers to design and launch AI solutions end-to-end.
• Communicate complex technical ideas clearly to stakeholders.
• Stay current with advancements in ML modeling techniques.
• Hire and grow a science team in the video personalization domain.

Skills

PhD/MA+ yrs exp

Science leadership

Applied ML research

ML/NLP/IR analytics

Java/C++/Python

Communication skills

Education

PhD or MS + 6+ yrs research

Tools

Java

C++

Python

Job description

Amazon.com Services LLC is seeking an Applied Science Manager for Prime Video Personalization & Discovery. You will lead a science team and partner with engineers, product managers, and business partners to deliver state-of-the-art personalized experiences for Prime Video across devices.

You will shape the product, roadmap, and technology choices, while hiring and growing the team, impacting millions of customers globally with personalized content recommendations.