Applied Scientist, Fashion & Fitness

At Fashion/Fitness & Cross-category tech, we leverage advanced AI technologies, including the latest Large Language Models (LLMs) and Generative AI (GenAI), to build ranking and recommendation models to help customer find New and High-value products that are on-trend, in-season, and in alignment with consumers’ interests.

We're seeking innovative Applied Scientists passionate about leveraging advanced AI to tackle complex challenges in product intelligence, data integration, and knowledge discovery. In this role, you'll collaborate with our principal applied scientists, as well as teams across Amazon to drive customer-focused solutions and amplify the impact of your work on our global customer base.

Key job responsibilities
- Design and implement advanced AI models using the latest LLM and GenAI technologies to enhance product understanding, matching at unprecedented scale.

- Develop novel approaches to extract, generate, and validate product and customer attributes and relationships using multimodal AI, combining text, image, and structured data analysis.

- Create intelligent systems that can automatically surface high-quality products from large candidate pool.

- Implement advanced natural language processing and computer vision models to extract insights from diverse data sources, including web content, user-generated data, and product imagery.

- Develop innovative solutions for entity resolution, knowledge graph construction, and semantic reasoning to build a comprehensive understanding of the global product landscape.

- Collaborate with cross-functional teams to integrate AI-driven insights into Amazon's product selection strategies and decision-making processes.

- Lead the design and implementation of scalable, production-ready AI systems that can process billions of products efficiently on Amazon Web Services (AWS).

- Stay at the advance of AI research, continuously exploring and implementing new techniques in LLMs, GenAI, and multimodal learning to drive innovation in product intelligence.

- Contribute to the scientific community through publications, presentations, and collaborations with academic institutions.

Basic Qualifications

- 4+ years of applied research experience
- 3+ 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

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.

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.