Applied Scientist II, Sponsored Products Global Optimization

Amazon • Seattle, WA

5d

About The Position

Global Optimization is a strategic initiative aimed at improving Amazon
advertisers experience at global scale. We are looking for a passionate Applied
Scientist to help pioneer the next generation of agentic AI applications for
Amazon advertisers. In this role, you will design agentic architectures, develop
tools and datasets, and contribute to building systems that can reason, plan,
and act autonomously across complex advertiser workflows at global scale. You
will work at the forefront of applied AI, developing methods for fine-tuning,
reinforcement learning, and preference optimization, while helping create
evaluation frameworks that ensure safety, reliability, and trust at scale.

You will work backwards from the needs of advertisers—delivering customer-facing
products that directly help them create, optimize, and grow their campaigns.
Beyond building models, you will advance the agent ecosystem by experimenting
with and applying core primitives such as tool orchestration, multi-step
reasoning, and adaptive preference-driven behavior. This role requires working
independently on ambiguous technical problems, collaborating closely with
scientists, engineers, and product managers to bring innovative solutions into
production.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the
advertising landscape through the latest generative AI technologies,
revolutionizing how millions of customers discover products and engage with
brands across Amazon.com and beyond. We are at the forefront of re-inventing
advertising experiences, bridging human creativity with artificial intelligence
to transform every aspect of the advertising lifecycle from ad creation and
optimization to performance analysis and customer insights.

We are a passionate group of innovators dedicated to developing responsible and
intelligent AI technologies that balance the needs of advertisers, enhance the
shopping experience, and strengthen the marketplace.

The Global Optimization team within Sponsored Products and Brands is focused on
guiding and supporting 1.6MM advertisers to meet their advertising needs of
creating and managing ad campaigns at global scale. At this scale, the
complexity of diverse advertiser goals, campaign types, and market dynamics
creates both a massive technical challenge and a transformative opportunity:
even small improvements in guidance systems can have outsized impact on
advertiser success and Amazon’s retail ecosystem.

Our work is grounded in state-of-the-art agent architectures, tool integration,
reasoning frameworks, and model customization approaches (including tuning, MCP,
and preference optimization), ensuring our systems are both scalable and
adaptive.

Requirements

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• 3+ years of building models for business application experience
• Experience programming in Java, C++, Python or related language
• Experience in designing experiments and statistical analysis of results

Nice To Haves

• Experience in professional software development
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
• Experience with LLMs, AI Agents, MCPs, Chain of Thought reasoning

Responsibilities

• Design and build agents that improve advertisers experiences globally
• Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).
• Design and implement optimization models that work at global scale taking into account nuances of multiple countries
• Innovate new science models to help advertisers scale their campaigns globally
• Curate datasets and tools for MCP.
• Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.
• Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning.
• Prototype and iterate on multi-agent orchestration frameworks and workflows.
• Collaborate with peers across engineering and product to bring scientific innovations into production.
• Stay current with the latest research in LLMs, RL, and agent-based AI, optimization and translate findings into practical applications.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree