Applied Scientist II, Visual Search Science

About the role

The Applied Scientist II for Visual Search Science will 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. They will 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. A core part of the role involves building LLM-based classifiers for visual intent detection, query understanding, and safety filtering within real-time latency budgets. They will advance AI safety science through defense-in-depth approaches including embedding-space classifiers, adversarial data engines, and post-generation content moderation. They will 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. They will collaborate with engineering, product, and design teams to architect GPU-intensive inference pipelines serving real-time traffic at scale, and contribute to Amazon's scientific community through publications and patents.

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, and contribute to Amazon's scientific community through publications and patents.

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

Qualifications

• 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

Benefits

Amazon 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.