Head of LLM & GenAI for Ad Creatives

The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (text, audio, images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related methods. You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially with LLMs, generative audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team. Key job responsibilities This role is focused on LLMs and the related foundational models to augment generative imagery and videos. You must have deep technical experience working with methods and technologies related to Large Language Models (LLMs), from model fine-tune to prompt engineering. A strong developing machine learning background is preferred, in addition to experience building LLMs applications and research. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. As LLMs Applied Scientist on this team, you will: Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity. Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. Run A/B experiments, gather data, and perform statistical analysis. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. Identify and action data collection and labelling in conjunction with team members. Research new and innovative machine learning approaches. Mentor and help recruit Applied Scientists to the team. Present results and explain methods to senior leadership. Willingness to publish research at internal and external top scientific venues. Write and pursue IP submissions. A day in the life Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. About the team The team is a growing team of applied scientists and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. We are open to hiring candidates to work out of one of the following locations: USA (Seattle, CA), UK (London, Bristol, Edinburgh) We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA 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 Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Experience with neural deep learning methods and machine learning Experience with LLM model training and tuning PREFERRED QUALIFICATIONS Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field. Published relevant research work in academic conferences or industry circles. Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc. Effective verbal and written communication skills with non-technical and technical audiences. Experience working with large real-world data sets and building scalable models from big data. Thinks strategically, but stays on top of tactical execution. Exhibits excellent business judgment; balances business, product, and technology very well. Experience in computational advertising. 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/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. Applicants should apply via our internal or external career site. #J-18808-Ljbffr