Applied Scientist II, Visual Search Science
Amazon
- Seattle, Washington, United States
- Seattle, Washington, United States
About
Amazon Search is building a first-of-its-kind AI-powered visual search experience that lets customers describe products they’re imagining, instantly see AI-generated images in response, and tap those images to search for matching products to shop. We are transforming the search engine into a shopping engine by leveraging advances in generative AI and multimodal understanding.
We are seeking an Applied Scientist II to join the Visual Search Science team and push the boundaries of generative AI and multimodal retrieval at Amazon scale. You will work at the intersection of diffusion models, large language models (LLMs), and multimodal search to build systems that generate product visualizations in real time and connect them to Amazon’s billions‑scale catalog. The ideal candidate has deep expertise in one or more of the following areas: text-to-image generation, multimodal retrieval, LLM-based classification, AI safety and content moderation, or retrieval-conditioned generation.
Key Job Responsibilities
Design, train, and optimize generative AI models for real‑time product image generation, ensuring outputs meet strict latency requirements while maintaining high visual quality and query alignment.
Develop multimodal retrieval systems that connect AI-generated images to Amazon’s billions-scale product catalog, optimizing for recall and ranking relevance across product categories.
Build LLM-based classifiers for visual intent detection, query understanding, and safety filtering within real‑time latency budgets.
Advance AI safety science through defense-in-depth approaches including embedding-space classifiers, adversarial data engines, and post-generation content moderation.
Design and execute large-scale online experiments to measure impact on customer engagement, search success, and business metrics, defining evaluation frameworks that combine automated metrics with human judgment.
Collaborate with engineering, product, and design teams to architect GPU-intensive inference pipelines serving real‑time traffic at scale.
Contribute to Amazon’s scientific community through publications and patents.
About the Team The Visual Search Science team pioneers generative AI for shopping within Amazon Search. We sit at the intersection of computer vision, natural language processing, and information retrieval, building systems that help customers visualize what they’re looking for and seamlessly discover matching products. Our team operates with speed and autonomy while leveraging Amazon’s massive scale, GPU infrastructure, and product catalog. We are a tight-knit group of scientists and engineers who value rigorous experimentation, creative problem‑solving, and shipping innovations that customers love.
Basic Qualifications
PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience.
Experience programming in Java, C++, Python or related language.
Experience in state-of-the-art deep learning model architecture design, training and optimization, and model pruning.
Preferred Qualifications
Experience using Unix/Linux.
Experience in professional software development.
Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms.
Publications at top-tier conferences such as CVPR, ICCV, ECCV or NeurIPS.
Salary and Location Location: Palo Alto, CA (USA)
Annual Salary: 171,600.00 – 222,200.00 USD
Equal Opportunity Employment Statement 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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Languages
- English
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