Are you an inventive, curious, and driven Applied Scientist with a strong background in AI and Deep Learning? Join Amazon’s AWS Multimodal generative AI science team and be a catalyst for groundbreaking advancements in Computer Vision, Generative AI, and foundational models.As part of the AWS Multimodal generative AI science team, you’ll lead innovative research projects, develop state-of-the-art algorithms, and pioneer solutions that will directly impact millions of Amazon customers. Leveraging Amazon’s vast computing power, you’ll work alongside a supportive and diverse group of top-tier scientists and engineers, contributing to products that redefine the industry.Key job responsibilities* Lead research initiatives in Multimodal generative AI, pushing the boundaries of model efficiency, accuracy, and scalability.* Design, implement, and evaluate deep learning models in a production environment.* Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services.* Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation.* Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence.Basic Qualifications- Ph.D. or Master’s in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.- Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models.- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms.- Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java).- First author in research publications in peer-reviewed conferences or journalsPreferred Qualifications- Experience designing and leading complex research projects from ideation to implementation.- Deep understanding of statistical modeling, optimization, and algorithm development.- Excellent communication skills, with the ability to convey complex technical information to diverse audiences.