Applied Scientist II, Sponsored Products and Brands - Advertiser Growth and Strategies

AI in this role

Applied Scientist II building agentic AI systems for automated advertising campaign optimization.

machine-learningapplied-scienceagentic-systemsoptimizationpython

We are looking for an Applied Scientist II to build the AI behind Auto Optimization: agentic systems that automatically optimize advertisers' campaigns on their behalf. Guided by an advertiser's standing instructions, these agents observe how a campaign is performing, reason about what to change, and act on it continuously as conditions in the marketplace shift.

Optimizing a campaign well is a collection of decisions. It means working across every control an advertiser has at once: the keywords and products they target, the bids they set, the budgets they allocate, and where their ads appear, all aligned with the preferences of the advertiser. These choices are connected, since a change to targeting changes the right bid, and a change in bids changes how budget should be spent. You will build agents that make these decisions together rather than one lever at a time, and that adapt across many different campaign types and advertiser goals, from growing sales on established products to reaching new customers and launching new ones.

Working backwards from the needs of millions of advertisers, you will solve ambiguous problems, invent new methods, and deliver them into a live product that manages real campaigns. You will stay deeply hands-on with the hardest technical problems, collaborate with product and engineering partners on approach, and help raise the quality of the team's science.

Key job responsibilities
- Build agentic systems that automatically optimize campaigns on an advertiser's behalf, working holistically across every control they have (targeting, bids, budgets, and placements) rather than one lever at a time, and generalizing across many campaign types and advertiser goals, from scaling a proven product to reaching new customers and launching something new.
- Encode the dynamics of the auction and marketplace into how the agent reasons, balancing advertiser return, shopper experience, and marketplace health.
- Turn raw signal into intelligence by defining and curating the datasets that train and evaluate these agents, from campaign and marketplace data to auction and bid/budget signals, impressions, clicks, conversions, and search-term performance.
- Push the frontier of agent design, building the core of the agent itself: planning, tool use (for example, auction simulation, ML models, and optimization routines), and long-horizon reasoning across decisions that interact, and writing the production-quality, critical-path code that carries it from prototype to launch.
- Set the bar for trust by developing the evaluation and safety methods that make it trustworthy to let an agent act on live campaigns and real budgets.
- Grow with a team that grows the field: contribute to our scientific agenda, learn alongside strong scientists and engineers, and share your work with the broader community.

About the team
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. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

This team within Sponsored Products and Brands is focused on guiding and supporting millions of advertisers to meet their advertising needs of creating and managing ad campaigns. 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 vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as autonomously managing campaigns based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities, from high-level product guidance down to granular keyword recommendations, and deliver them through a tailored, personalized experience. 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.

Basic qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred qualifications

- Experience using Unix/Linux
- Experience in professional software development
- Experience building high-velocity ad products
- Experience designing and deploying LLM-based agents in production.

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also 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. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 172,400.00 - 223,400.00 USD annually
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist II, Sponsored Products and Brands - Advertiser Growth and Strategies at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Machine LearningApplied ScienceAgentic SystemsOptimizationPython

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where applied science was part of your work. What did you do?
Tell me about a project where agentic systems was part of your work. What did you do?
Tell me about a project where optimization was part of your work. What did you do?
Tell me about a project where python was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine Learning, Applied Science, Agentic Systems, Optimization, and Python. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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