Senior Applied Scientist, Agentic Ad AI

Amazon; Palo Alto (CA); On-site; USD 192,000 - 260,000; Full time

Job summary

Amazon Ads is building the next generation of agentic AI to guide advertisers, blending research depth with practical product impact. As an Applied Scientist III, you will define the science direction for autonomous ad campaign management and partner with product and engineering leaders to translate vision into concrete roadmaps.

You will work on medium-to-large, ambiguous problems at scale, invent new methods, mentor scientists and engineers, and stay hands-on with core code as you shape the

Qualifications

• 5+ years of building machine learning models for business applications.
• PhD, or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related languages.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Define the science vision for the agentic campaign management system and turn it into delivery roadmaps.
• Build agentic systems that autonomously manage and optimize ad campaigns.
• Define and curate the datasets and signals needed to train and evaluate these agents.
• Stay hands‑on: write production‑quality, critical‑path code.
• Own the agentic architecture and long‑horizon reasoning, and write production‑quality code from prototype to launch.
• Define the evaluation and safety methodology for agent workflows and drive its adoption.
• Drive the team’s scientific agenda, mentor scientists and engineers.

Skills

ML model building

Deep learning

Programming: Java/C++/Python

Applied research

Education

PhD

Master's degree + 6+ years experience

Job description

Amazon Ads is building the next generation of agentic AI to guide advertisers, blending research depth with practical product impact. As an Applied Scientist III, you will define the science direction for autonomous ad campaign management and partner with product and engineering leaders to translate vision into concrete roadmaps.

You will work on medium-to-large, ambiguous problems at scale, invent new methods, mentor scientists and engineers, and stay hands-on with core code as you shape the