Applied Scientist II, Visual Search Science
About The Position
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. You will operate with startup-level autonomy backed by the resources of Amazon Search, serving hundreds of millions of customers worldwide.
Requirements
- 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 models architecture design and deep learning training and optimization and model pruning
Nice To Haves
- Experience using Unix/Linux
- Experience in professional software development
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
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.
Benefits
- 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
- parental leave
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
