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# Engineering Manager, Core Personalization Systems

- **Company:** Netflix, Inc.
- **Location:** Los Gatos, CA, United States
- **Experience:** Experienced
- **Salary:** $190,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), A/B Testing, Cloud Computing, Information Engineering, Distributed Systems, Machine Learning, Backend, Information Technology, Low Latency
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_05f920117d024c89f5d95d86af43b016

## About the Role

* 3 years of people management experience
 * A track record of hiring diverse, highly talented engineers and growing successful, highly impactful teams
 * A passion for improving consumer experiences through strong partnerships with product leaders, ability to influence product direction and roadmaps
 * Excellence in communicating context with the team, stakeholders, partners, and leadership. Ability to drive the team's roadmap by connecting the dots between your team's work and business needs, managing expectations, and navigating competing priorities
 * Domain experience with personalization, AB testing, machine learning, cloud computing, and Java
 * Strong technical acumen and ability to act as a technical advisor to the team. Experience building and operating distributed systems with a direct impact on the customer experience
 * A leadership style that prioritizes giving and receiving feedback, fostering new ideas, and empowering others without micromanagement
 * A BS in Computer Science/Engineering or a related discipline

## Description

Our org is responsible for backend distributed systems that drive core aspects of the discovery experience like content and asset personalization and search. The teams are responsible for large scale offline systems as well as very high throughput, low latency systems that deliver personalized data in real-time to Netflix UI clients. The teams are involved in experimentation to continuously evolve the member experience as well as in developing foundational systems that help us accelerate innovation. We partner with a large set of cross-functional teams like ML researchers, Product Management, Content Creative teams, Product Design, Data Engineering, and many backend and client engineering teams.