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Principal Applied Scientist, FAIM; Funnel Agentic Intelligence and Models

Job in Seattle, King County, Washington, 98194, USA
Listing for: Amazon
Full Time position
Listed on 2026-10-31
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Position: Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models)
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 product ionize 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.

Basic Qualifications

-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

Preferred Qualifications

-10+ years of relevant work in industry or academia experience

-Knowledge of problem solving, algorithm design and complexity analysis

-Experience creating novel algorithms and advancing the state of the art

-Have peer-reviewed scientific contributions in premier journals and conferences

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions;…
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