Machine Learning Scientist - GenAI, KIT

AWS Applied AI Solutions AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset. At AWS we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it and help customers adopt best practices while architecting on the cloud. We are looking for Applied Scientists to drive innovation with Gen AI to bring paradigm shift to how the business operates and build "best in the world" experience that customers will love! Some of the science challenges we work on include building Agentic AI systems, fine-tuning Large Language Models for domain-specific use cases, Reinforcement Learning, automated cloud optimization, and generating strategic insights and recommendations from very large datasets. You will have an opportunity to lead invent and design tech that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system. Our team packs a punch with principal level product science engineering and leadership talent. We are a results focused team and you have the opportunity to lead and establish a culture for the big things to come. We combine the culture of a startup the innovation and creativity of a R&D Lab the work-life balance of a mature organization and technical challenges at the scale of AWS. We offer a playground of opportunities for builders to build have fun and make history! About AWS: About the team Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Basic Qualifications - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building models for business application experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Experience in professional software development A W S