Applied Scientist II, GenAI Evaluation Media (GEM)

Key job responsibilities

• Develop core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI
• Design and implement visual agentic systems, balancing visual quality, relevance, latency, and cost
• Define metrics and success criteria for your scientific initiatives, ensuring rigorous validation across customer touch points
• Own end-to-end delivery of research initiatives from problem formulation through experimentation to production deployment
• Stay current with latest advances in AI/ML and identify opportunities to apply them to your problem space
• Drive development and deployment of scalable agentic systems for visual content understanding and generation
• Maintain high scientific and engineering standards in your work
• Tackle complex technical problems while maintaining practical focus on customer value
• Contribute to the team's culture of scientific excellence through presentations and publications at internal and external science forums

Cross-functional Collaboration

• Partner with product and engineering teams to deliver customer-facing features
• Collaborate with scientists and engineers across multiple teams within Amazon to align on technical approaches
• Communicate research findings and technical trade-offs clearly to both technical and non-technical stakeholders

Basic Qualifications

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience in building models for business application
• Experience programming in Java, C++, Python or related language

Preferred Qualifications

• Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
• Experience in CS, CE, ML or related field research
• Experience building machine learning models or developing algorithms for business application
• Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
• Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
• Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.