The Community Feedback organization powers customer-generated features and insights that help customers use the wisdom of the community to make unregretted shopping decisions. Today our features include Customer Reviews, Content Moderation, and Customer Q&A (Ask), however our mission and charter are broader than these features. We are focused on building a rewarding and engaging experience for contributors to share their feedback, and providing shoppers with trusted insights based on this feedback to inform their shopping decision
The Community Data & Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a background in AI, Gen AI, Machine Learning, and NLP to help build LLM solutions for Community Feedback. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team and are ready to make a lasting impact on the future of AI-powered shopping, we invite you to join us on this exciting journey to reshape shopping.
Please visit https://www.amazon.science for more information.
Key job responsibilities
- As a Senior Applied Scientist, you will work on state-of-the-art technologies that will result in published papers.
- However, you will not only theorize about the algorithms but also have the opportunity to implement them and see how they perform in the field.
- Our team works on a variety of projects, including state-of-the-art generative AI, LLM fine-tuning, alignment, prompt engineering, and benchmarking solutions.
- You will be also mentoring junior scientists on the team.
About the team
The Community Data & Science team focusses on analyzing, understanding, structuring and presenting customer-generated content (in the form of ratings, text, images and videos) to help customers use the wisdom of the community to make unregretted purchase decisions. We build and own ML models that help with i) shaping the community content corpus both in terms of quantity and quality, ii) extracting insights from the content and iii) presenting the content and insights to shoppers to eventually influence purchase decisions. Today, our ML models support experiences like content solicitation, submission, moderation, ranking, and summarization.
- 3+ years of building machine learning models for business application experience.
- PhD, or Master's degree and 5+ years of applied research experience.
- Experience programming in Java, C++, Python or related language.
- Experience with neural deep learning methods and machine learning.
- PhD and 7+ years of post-PhD academic or industry applied research experience in building and deploying models for business applications.
- Experience with professional software development
- Publications at top-tier peer-reviewed conferences or journals
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