Machine Learning Scientist 6 - Ads Member Understanding

Netflix•Los Angeles, CA

40d•$600,000 - $1,066,000

About The Position

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. 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. We launched a new ad-supported tier in November 2022 and are building an in-house, world-class ad tech ecosystem to give our members more choices in how they enjoy Netflix. This tier lets us attract new members at a lower price point while creating a compelling path for advertisers to reach deeply engaged audiences. This role sits within the Ad Ranking org inside Ads Data Science and Engineering (DSE). Ad Ranking's key areas of focus span Identity Matching, Audience & Targeting, User Understanding, Relevance & Engagement Prediction, and Bidding & Pacing - the ML systems that decide which ad reaches which member, and when. We're hiring a Machine Learning Scientist 6 to lead our user understanding charter. This person will leverage Netflix’s rich multimodal signals and LLM techniques to build a user-understanding foundation for the ads team. It will be used both as a feature foundation for ad targeting, ranking, and bidding. They'll also shape our 1P and 3P data strategy as the platform evolves, and will have latitude to partner across the broader Ads ML org.

Requirements

Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent industry experience.
7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior-staff-level scope and impact.
Track record building user or audience understanding systems - embeddings, representation learning, identity resolution, or similar - ideally in a monetization or ads context.
Hands-on experience applying LLM to user modeling, content understanding, or recommendation, with good judgment on where these approaches beat traditional methods.
Proficiency in Python, Scala, or Java, and experience prototyping and deploying models on large-scale production data.
Strong business acumen and the ability to translate technical results into business impact.
Excellent communication and cross-functional collaboration skills.

Nice To Haves

Influence 1P/3P data strategy, privacy-aware data usage, or identity/targeting infrastructure is a strong plus.
A track record of setting technical direction and influencing roadmap across teams; experience as a vertical or xfn technical lead is a strong plus.

Responsibilities

Set the technical direction for user understanding by leveraging multimodal signals - from content, viewing behavior, and context.
Shape and land Netflix's data strategy for a fast-growing team, partnering with privacy, legal, and platform engineering to build a data foundation that scales.
Partner with the ranking, bidding & pacing teams to get user-understanding signals into production and drive downstream impact.
Build rigorous online and offline evaluation frameworks to quantify the incremental value of new signals, representations, and models.
Communicate technical strategy, trade-offs, and results to both technical and non-technical audiences, including senior leadership