Overview In this role, you will advance GenAI and multimodal AI to infer product identities and relationships at scale for Amazon's catalog. You will work with cross-functional partners to translate business challenges into robust models and deploy them for billions of products and customers. You will build end-to-end ML pipelines, apply explainable AI, and shape research roadmaps that balance foundational work with pragmatic product impact. You will mentor peers and share findings to keep the team at the forefront of GenAI and multimodal AI. This is a high-impact role that blends cutting-edge research with production-scale delivery.
Compensation / Benefits- health insurance (medical, dental, vision, prescription)
- 401(k) matching
- paid time off
- parential leave
- RSUs and sign-on payments
- comprehensive benefits package
Responsibilities- Formulate research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval
- Design and implement models using VLMs, foundation models, and agentic architectures for product identity and catalog understanding at billion-product scale
- Develop explainable AI methodologies balancing performance with production scalability
- Own end-to-end ML pipelines from ideation to production deployment processing petabytes of multimodal data
- Define research roadmaps aligned with business priorities and product improvements
- Mentor scientists and engineers on advanced ML techniques and experimental rigor
- Represent the team through publications, talks, and ongoing leadership in GenAI and multimodal AI
Key requirements- PhD, or Master's degree with 4+ years of CS, CE, ML or related field experience
- Proficiency in Java, C++, Python or related language
- collaboration
- mentoring
- experimental design
- GenAI
- multimodal learning
- visual language models (VLMs)
