Senior Applied Scientist, Sponsored Products and Brands
6 giorni fa
Senior Applied Scientist, Sponsored Products and Brands Job ID: | Amazon.com Services LLC The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace ecosystem. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key ResponsibilitiesDevelop AI solutions for Sponsored Brands advertiser and shopper experiences; build recommendation systems that leverage generative models to develop and improve campaigns. Invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. Drive or heavily influence the design of scientifically-complex software solutions or systems, personally writing significant parts of the critical scientific novelty and providing a system-wide view and design guidance. Define a long-term science vision and roadmap for our Sponsored Brands advertising business, translating direction into specific plans for applied scientists and engineering teams. Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end. Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. Think big about the arc of development of Gen AI over a multi-year horizon, identifying new opportunities to apply these technologies to solve real-world problems. Effectively communicate technical and non-technical ideas with teammates and stakeholders. Translate complex scientific challenges into clear and impactful solutions for business stakeholders. Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. Stay up-to-date with advancements and the latest modeling techniques in the field.About the Team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale. Basic Qualifications3+ 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 Deep curiosity, and basic knowledge on Gen AIPreferred QualificationsExperience 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. Previous work on agents or LLMsAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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. #J-18808-Ljbffr
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