Engineering Manager, Ads Signals & Targeting

Netflix
New York,New York,United States of America / Los Gatos,California,United States of America2026-04-27onsite

About the job

At Netflix, our mission is to entertain the world. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. The Ads Engineering team at Netflix is dedicated to creating a world-class advertising ecosystem that drives our advertising business. This team's mission is to develop advanced technology that ensures exceptional experiences for both our members and advertisers. Our responsibilities encompass a broad spectrum of products, ranging from sales and media planning to optimizing advertiser outcomes and execution. We use several Netflix investments and innovations - a unique mix of client and server-side ad insertions, state-of-the-art content delivery systems, ad encoding recipes, content understanding, and metadata, etc. We deliver ads in a manner that’s thoughtful of our member’s viewing experience and drive great outcomes for advertisers. We also ensure that advertiser brand safety is ensured during serving so that members only see the most appropriate ads for them.

Responsibilities

Own the core signals and targeting systems that power relevant ads for Netflix members.

Start from a solid foundation, with significant room to evolve the platform.

Partner closely with ML teams to build advanced interest, lookalike, and expansion models.

Work on high-scale, low-latency services that enrich every ad request in real time.

Shape how Netflix activates first‑party and partner signals for targeting, optimization, and measurement.

Drive success in a fast paced, flat organization with minimal process and a heavy emphasis on ownership.

Support your team by contextualizing the larger vision, enabling prioritization and fostering high focus and executional excellence.

Operate as an ambassador of the Netflix Culture

Create a dream team by hiring, retaining, and growing high performing talent.

Qualifications

Minimum

Proven experience leading teams that build and operate high-throughput, low-latency distributed systems in ads targeting, or similarly demanding domains

Hands-on background with signal services for ad request enrichment, including real-time and batch data integration

Strong familiarity with contextual and profile-based signals and how they are used for audience and contextual targeting

Experience designing and managing signals registration, governance, and curation frameworks

Expertise with targeting and audience definition metadata (e.g., taxonomies, hierarchies, schemas, configuration management)

Experience leading ML engineers building and operating modeled profile audiences and lookalike models, including taking these models from development through integration into production systems.

Track record of building and leading high-performing engineering teams, setting technical direction, and delivering complex platform initiatives

Ability to navigate ambiguity and define clear strategies in a fast-evolving ads landscape

Excellent communication skills; you can explain complex systems to both technical and non-technical partners

10+ years of total experience with 3+ years of management experience in building and leading diverse software engineering teams.

A strong product mindset along with experience in delivering large complex projects collaborating with a variety of cross-functional stakeholders that are technology, operations or business focused.

General understanding of the advertising marketplace and landscape.

Strong analytical and strategic thinking with demonstrated product sense and leadership in the working environment

Preferred

Familiarity with legal compliance and changing landscape of ads regulations around the world.

Familiarity with ML and advertising systems that leverage data to drive optimal outcomes for the users and the business.

Experience working in the CTV space and knowledge of its unique constraints