Applied Scientist II

Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we use machine learning and cluster-computing technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing . The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment.
We are looking for Applied Scientists to tackle challenging problems in the areas of high scale data processing, quality & natural language based information retrieval from data . You will encounter many challenges, including

• Scale (build models to handle billions of records)
• Accuracy (High precision and recall requirements) in deduplication and anomaly detection
• Diversity (models need to work across different data formats, languages, and sources)

You will help us to

• Build scalable systems for intelligent catalog management using ML/AI-based deduplication and entity resolution
• Develop advanced anomaly detection frameworks to identify data quality issues and inconsistencies across large datasets.
• Build knowledge graph-based solutions to enhance data relationships and improve consumption of structured and unstructured data for consumers at scale.

Key job responsibilities
Use AI, NLP and advances in LLMs/SLMs to create scalable solutions for business problems

• Design, develop, evaluate and deploy, innovative and highly scalable ML models
• Work closely with software engineering teams to drive real-time model implementations
• Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance
• Leading projects and mentoring other scientists, engineers in the use of ML techniques