Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Experience
- Senior Level 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
- Education
- PhD, or Master's degree and 6+ years of applied research experience
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Role Summary
Senior Applied Scientist on the Sponsored Products Search Sourcing Science team at Amazon Ads, working on generative AI and machine learning to improve retrieval and ranking of sponsored products for shopper queries. The role serves as technical leader in ML and GenAI and leads end-to-end ML projects from problem definition to production.
What You'll Do
- 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.
- Apply LLM knowledge (prompt engineering, fine-tuning, RAG, evaluation) to build production-grade GenAI applications.
- Design and run A/B experiments, and perform statistical analysis to measure impact and guide decisions.
- Recruit, mentor, and grow Applied Scientists on the team.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 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...
Preferred
- 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 in machine learning, data mining, information retrieval, statistics or natural language processing, or experience leading...
- 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.