Sr. Applied Scientist, Ads AI Core Infrastructure (Advertising)

Sr. Applied Scientist, Ads AI Core Infrastructure
Job ID: 10380588 | Amazon.com Services LLC

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering AI-powered solutions that transform how advertisers make strategic decisions. We deliver billions of ad impressions and process massive volumes of advertiser data every single day. You'll work with us to pioneer breakthrough approaches in how AI agents access and reason over real-time advertiser data at scale.

We are using generative AI and agentic systems to help advertising agents provide instant, strategic advice to millions of advertisers. You will need to invent new techniques for agent orchestration, context optimization, and code generation to ensure we're delivering accurate, trustworthy insights with minimal latency and token consumption. You'll create feedback loops to ensure our solutions are constantly evaluating themselves and improving.

Key Job Responsibilities

Agent Orchestration & Optimization Research

Research and develop novel algorithms for agent-data interaction patterns that minimize latency, token consumption, and error rates.

Investigate multi-agent orchestration strategies for complex advertiser queries requiring data from multiple sources.

Develop techniques for automatic query optimization and caching strategies based on agent behavior patterns.

Large Language Model Context & Token Optimization

Invent new methods for compressing advertiser context representations while preserving semantic meaning and analytical utility.

Research optimal metadata generation techniques that help large language models understand and reason over structured advertiser data.

Design evaluations to measure the impact of different data representations on agent response quality and token efficiency.

Develop adaptive context selection algorithms that dynamically choose relevant data based on query intent.

RAG-Based Embeddings & Semantic Search

Pioneer new RAG-based embedding approaches optimized for real-time advertiser data delivery with sub-second latency.

Research and implement semantic search and retrieval techniques for advertiser datasets using vector embeddings.

Design advertiser context frameworks that enable automatic schema mapping from advertiser concepts to data representations.

Develop evaluation frameworks to measure performance across dimensions of latency, accuracy, and developer experience.

Experimentation & Productionization

Design and execute rigorous experiments comparing traditional API orchestration versus CodeAct patterns and RAG-based approaches across metrics like success rate, latency, token consumption, and response quality.

Analyze large-scale advertiser interaction data to identify patterns, bottlenecks, and optimization opportunities.

Collaborate with engineering teams to productionize research innovations and deploy them to 30+ advertising agents and skills.

Establish evaluation metrics and benchmarks for agent-data interaction performance.

Cross-Functional Collaboration & Thought Leadership

Partner with agent builder teams to understand their data requirements and constraints.

Work with platform engineers to implement and optimize MCP servers, data pipelines, and sandbox execution environments.

Collaborate with product managers to translate research insights into product features and roadmap priorities.

Stay current on latest advancements in agentic AI research, specifically in large language models, multi-agent systems, chain of thought reasoning, and autonomous agents.

Research Publication & Innovation

Author technical papers for top-tier conferences on agent orchestration, context optimization, RAG-based embeddings, and real-time data integration.

File patents for novel techniques in agent-data interaction, token optimization, and CodeAct patterns.

Present research findings at internal tech talks and external conferences.

Mentor engineers and junior scientists on machine learning techniques, experimental design, and research methodologies.

About the Team
The Ads Real-Time Data Service team is a diverse group of passionate engineers and scientists dedicated to advancing agent-data interaction technology for advertising AI. We value creativity, collaboration, and a commitment to excellence. Our team thrives on tackling complex problems at the intersection of real-time data engineering, AI agent systems, and large language model optimization—turning innovative research ideas into production systems that serve millions of advertisers.

We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. We have a broad mandate to experiment and innovate, working on problems in agentic AI, context optimization, RAG-based embeddings, and real-time data delivery.

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

Preferred Qualifications

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

Experience with large scale distributed systems such as Hadoop, Spark etc.

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. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Benefits
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.

Salary – 192,200.00 – 260,000.00 USD annually (USA, CA, Palo Alto)

Salary – 183,800.00 – 248,700.00 USD annually (USA, NY, New York)

Salary – 167,100.00 – 226,100.00 USD annually (USA, WA, Seattle)

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

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