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Amazon Systems Development Manager Kuiper Identity Infrastructure 
United States, Washington, Bellevue 
565628599

Today
Description

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Key job responsibilities
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:* Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.
* Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.
* Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.
* Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.
* Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.A day in the life

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
- Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.


Preferred Qualifications

- Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.
- Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.
- Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).
- Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.
- Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.
- Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.