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Machine Learning Engineer for Community Feedback
hace 2 meses
This is a high-level software engineering position that focuses on building state-of-the-art technologies to support the Community Feedback organization at Amazon. Our team works on various projects, including generative AI, large language model fine-tuning, alignment, prompt engineering, and benchmarking solutions. Key Responsibilities
- Design and implement machine learning models that analyze, understand, structure, and present customer-generated content (ratings, text, images, videos) to help customers make informed purchase decisions.
- Collaborate with talented scientists and engineers to innovate and develop novel techniques for community content corpus shaping, insight extraction, and presentation.
- Mentor junior scientists on the team and contribute to the development of cutting-edge LLM solutions for business applications.
About the Team
The Community Data & Science team is dedicated to analyzing and presenting customer-generated content to facilitate informed purchasing decisions. We build and own ML models that support experiences like content solicitation, submission, moderation, ranking, and summarization. Today, our ML models are deployed in various features, including content generation, recommendation systems, and customer reviews.
BASIC QUALIFICATIONS
- 3+ years of experience building machine learning models for business applications
- PhD or Master's degree with 5+ years of applied research experience
- Proficiency in programming languages such as Java, C++, Python, or related languages
- Experience with neural deep learning methods and machine learning frameworks
PREFERRED QUALIFICATIONS
- PhD with 7+ years of post-PhD academic or industry experience in building and deploying models for business applications
- Expertise in professional software development and publication in top-tier peer-reviewed conferences or journals
- Familiarity with Amazon's technology landscape and culture
