Machine Learning Scientist (L6) - Live Ads

We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.

Our Team

The Ad Supply & Decisioning team within the Ads Data Science and Engineering (DSE) organization drives ads growth by expanding ad inventory, optimizing member-ad matching, and maximizing long-term yield. The team spans three pillars, Ad Forecasting, Ad Ranking, and Ad Marketplace, and supports all ad surfaces, including live events such as sports, award shows, and cultural moments watched simultaneously by tens of millions of members around the world. Live advertising introduces a distinct class of problems: massive, unpredictable traffic spikes, global simultaneous delivery, hard real-time latency constraints, and the need to balance yield across direct and programmatic demand channels.

We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our core Live Ads ML problem areas - forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization. In this role, you will partner directly with the Live Ads product team to define the ML technical roadmap and collaborate across horizontal pods within Ad Supply & Decisioning to drive solutions.

Responsibilities

• Define and drive the ML technical roadmap in close partnership with the Live Ads product team, aligning technical investments with business priorities and product direction.

• Collaborate across horizontal pods to architect and deliver ML solutions spanning forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization.

• Design and implement machine learning and optimization algorithms to improve ad quality and performance.

• Build, train, and evaluate models on large-scale production data.

• Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements.

• Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals.

• Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, including senior leadership.

Qualifications

• Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.

• 7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior staff-level scope and impact.

• Deep knowledge of machine learning, optimization, and data analysis techniques.

• Experience in ad optimization stack, e.g. targeting, ranking, bidding. Experience in Live ads is a huge plus.

• Proven ability to set technical direction and influence roadmap across teams; experience serving as a vertical or staff-level technical lead is a strong plus.

• Experience with prototyping and deploying algorithms using large-scale production data.

• Proficiency in Python, Scala, or Java.

• Strong business acumen and ability to translate technical results into business impact.

• Excellent communication and collaboration skills.