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

About the role

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 set up 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 training models in our RL Gym from end-to-end
• Invent models for joint budget allocation, incrementality, and long-term value
• Take innovations from prototype to production serving live advertiser campaigns
• Raise the technical bar across scientists and engineers

Responsibilities

• Define the long-term scientific vision for our RL Gym based training process focusing on campaign optimization and other advertising workflows
• 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

• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
• 5+ years of hands-on experience in predictive modeling and analysis
• Experience distilling informal customer requirements into problem definitions while dealing with ambiguity and competing objectives
• Experience programming in Java, C++, Python, or related language
• Experience leading experienced scientists, as well as a record of developing junior members from academia or industry into a career track in a business environment

Preferred Qualifications

• 10+ years of relevant experience in industry or academia
• Knowledge of problem solving, algorithm design, and complexity analysis
• Experience creating novel algorithms and advancing the state of the art
• Peer-reviewed scientific contributions in premier journals and conferences

Benefits

Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.

Pay

• USA, CA, Palo Alto: $228,700 – $309,400 annually
• USA, NY, New York: $218,800 – $295,900 annually
• USA, WA, Seattle: $198,900 – $269,000 annually

Base salary ranges vary by location. Total compensation includes sign-on payments and restricted stock units (RSUs); final compensation determined by experience, qualifications, and location.

Job ID: A10584104 | Company: Amazon.com Services LLC