Description The AWS Marketplace & Partner Services Science team is hiring an Applied Scientist to develop state-of-the-art recommendations systems, Conversational AI agents, and personalization capabilities within AWS Marketplace. This role will revolutionize discovery of solutions that accelerate customer cloud migrations for our customers, bringing personalization to AWS customers. The ideal candidate is comfortable leading production level recommendations strategies, implementing agent based conversationalAI experience, and mentoring other scientists on the team. You able to evaluate feasibility of scientific approaches and influence business leaders to develop the best experience for our customers. You thrive in a collaborative environment, where mentorship, learning, and teamwork is critical. Key job responsibilities - Work with customers, product managers, scientists, and engineers to deliver production level recommendation experiences - Ability to write production level code and support requirements for MLOps/LLMOps - Mentor Scientists on the team, and guide scientific approach across the organization About the team The AWS Marketplace & Partner Services Science team supports science models and recommendations that are deployed directly to AWS Customers (via AWS Marketplace), to our partners (via Partner Central), and to our internal AWS Sellers. Our mission is to accelerate cloud migrations and modernizations, supporting AWS customers to innovate, and the growth of our AWS Partners. Why AWS 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. Inclusive Team Culture 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 (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth 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. Diverse Experiences 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. Basic Qualifications - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 3+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Preferred Qualifications - Experience deploying recommendation models into production systems. - Experience leveraging Reinforcement Learning / Personalization within recommendations. - Experience with ConversationalAI Agents, ideally coupled with recommendations. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.