Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models)

Saved job description

The FAIM (Full Funnel Agentic Intelligence and Models) builds the agentic AI systems behind next-generation advertising. The team develops multimodal foundation models and LLM-driven agents that power shopper understanding, audience-aware creative generation, and agentic advertising workflows.

As a Principal Applied Scientist for the FAIM team, you will invent the models that help advertisers achieve desired outcomes. Today's state of the art models can setup ad campaigns to a specification, but do not understand advertising strategy well enough to help with abstract goals that real advertisers ask about like "how can I make more money."

This is a rare charter to build foundational optimization science where little exists today, spanning campaign recommendation, cross-product budget allocation, incrementality measurement, and long-term-sales modeling. You will set technical direction for a growing team, partner with engineering and product to take models from research to production at Amazon scale, and directly move advertiser ROAS and new-to-brand growth.

In this role you will

- Own the science vision for developing evaluations of the Ads Agent

- Partner with scientists from across Ads to develop best practices for evaluating agent performance both online and offline

- Raise the science bar for all agent evaluations developed in Ads.

- Own establishing a data driven foundation for making decisions about when new features are ready to launch in Ads Agent.

Key job responsibilities

- Define the long-term scientific vision for agent evaluations in Ads

- Translate ambiguous advertiser needs and competing objectives into a concrete science roadmap.

- Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase.

- Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value.

- Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction.

- Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production.

- Raise the technical bar across science and engineering through mentorship, design reviews, and hands-on collaboration.

- Grow scientific talent and publish impactful research internally and at top-tier venues.

Requirements: -5+ years of hands-on work in predictive modeling and analysis experience

-PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field

-Experience working in predictive modeling and analysis

-Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

-Experience programming in Java, C++, Python or related language

-Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment