Amazon advertisers need better guidance and support to create, optimize, and grow their campaigns. The complexity of diverse advertiser goals and market dynamics creates a technical challenge where improved guidance systems can significantly impact advertiser success and the Amazon retail ecosystem. The goal is to build a personalized, context-aware agentic advertiser guidance system leveraging LLMs and other tools.
Requirements
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Experience implementing algorithms using both toolkits and self-developed code
- Publications at top-tier peer-reviewed conferences or journals
Responsibilities
- Contribute to the design and development of agents that guide advertisers across conversational and non-conversational experiences.
- Implement and experiment with model and agent optimization techniques such as supervised fine-tuning and instruction tuning under the guidance of senior scientists.
- Support dataset curation and tooling for model customization and preference optimization (e.g., MCP pipelines).
- Build and maintain components of evaluation pipelines for agent workflows, including benchmark setup, automated test creation, and analysis of reasoning quality.
- Prototype and validate elements of agentic architectures (e.g., CoT, ReAct, or ToT) to improve planning, reasoning, and tool use.
- Conduct experiments, analyze performance, and communicate insights to drive iterative improvements to models and agents.
- Collaborate with scientists, engineers, and product managers to integrate research outputs into production systems.
Other
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- 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
- follow all federal, state, and local laws and Company policies
