Senior Applied Scientist, Sponsored Products

Amazon is hiring a Senior Applied Scientist, Sponsored Products in Seattle, United States. It pays $167k-$226k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
Pay on this posting starts in line with the typical applied scientist posting on Level.
The posting mentions prompt engineering, RAG and fine tuning among its tools and skills.
Amazon has 21,000+ other open roles on Level.
Posted in the last few days.

AI in this role

prompt-engineeringragfine-tuningnlpspeech

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge 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.

The Sponsored Products Search Sourcing Science (SPSSS) team's mission is to retrieve all relevant sponsored products in response to shopper queries, serving billions of daily ad impressions and tens of millions of clicks, helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this, we build state-of-the-art capabilities spanning query, shopper, product, and advertiser understanding, as well as advanced retrieval, targeting, and ranking systems, all powered by efficient large-scale data pipelines, deep learning, natural language processing (NLP), generative AI, and multi-agent workflows. It's a high-impact, technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.

Key job responsibilities
As a Senior Applied Scientist on this team, you will:
- Serve as the technical leader in Machine Learning and Generative AI, driving efforts within this team and across other teams.
- Lead end-to-end ML projects with high ambiguity, scale, and complexity—from problem definition to production.
- Build, optimize, and deploy ML models into production, partnering with software engineers to productionize solutions.
- Establish scalable, automated processes for data analysis, model development, validation, and serving.
- Apply strong knowledge of LLMs (prompt engineering, fine-tuning, RAG, evaluation) to build production-grade GenAI applications.
- Analyze large-scale data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Design and run A/B experiments, and perform statistical analysis to measure impact and guide decisions.
- Research and prototype innovative ML and GenAI approaches, bringing state-of-the-art techniques into production.
- Recruit, mentor, and grow Applied Scientists on the team.

About the team
Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

The Sponsored Products Search Sourcing Science (SPSSS) team's mission is to retrieve all relevant sponsored products in response to shopper queries, serving billions of daily ad impressions and tens of millions of clicks, helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this, we build state-of-the-art capabilities spanning query, shopper, product, and advertiser understanding, as well as advanced retrieval, targeting, and ranking systems, all powered by efficient large-scale data pipelines, deep learning, natural language processing (NLP), generative AI, and multi-agent workflows. It's a high-impact, technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.

Basic qualifications

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

Preferred qualifications

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Master's degree or above in engineering, statistics, computer science, mathematics, or a related quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience leading engineering teams as a mentor or tech lead
- Experience creating and delivering written and oral communications for technical and non-technical audiences
- Experience in data science, business analytics, business intelligence, or similar experience in big data environments
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business, product, and technology very well.
- Experience in computational advertising.
- Experience in Large Language Models (LLMs).

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; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually

How we rate this

Senior Applied Scientist, Sponsored Products at Amazon rates 96 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist, Sponsored Products is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $167k-$226k a year.
The role is based in US, WA, Seattle.
The job was posted on October 22, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGFine-tuningNLPSpeech

Also common in applied scientist jobs at this level

TensorFlow Spark Reinforcement learning Computer vision AWS scikit-learn

Pay

This job starts at: $167k
Typical applied scientist job: $172k

This posting starts close to the typical applied scientist job. See applied scientist jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
What NLP problem have you worked on, and how did you measure whether it actually worked?
What have you built with speech recognition or text-to-speech, and where did it break?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, NLP, and Speech. 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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