Sr. Applied Scientist, Intl Seller Growth

Sr. Applied Scientist, Intl Seller Growth Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer‑centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit for more information. Key job responsibilities Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language‑related challenges in the international seller services domain. Collaborate with cross‑functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high‑quality solutions. Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. Continuously explore and evaluate state‑of‑the‑art NLP techniques and methodologies to improve the accuracy and efficiency of language‑related systems. Communicate complex technical concepts effectively to both technical and non‑technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. Mentor and guide team of Applied Scientists from technical and project advancement stand point. Contribute research to science community and conference quality level papers. Basic Qualifications 5+ years of building machine learning models for business application experience PhD, or Master’s degree and 6+ years of applied research experience Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects) Preferred Qualifications Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large‑scale distributed systems such as Hadoop, Spark etc. Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr