Applied Scientist, Selection Monitoring

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 develop advanced ML/AI 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 Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale.

You will encounter many challenges, including:
- Scale (build models to handle billions of pages),
- Accuracy (requirements for precision and recall)
- Speed (generate predictions for millions of new or changed pages with low latency)
- Diversity (models need to work across different languages, market places and data sources)

You will help us to
- Build a scalable system which can algorithmically extract information from world wide web.
- Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web.
- Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents.


Key job responsibilities
- Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems.
- Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes.
- Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc.
- 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.
- Lead projects and mentor other scientists, engineers in the use of ML techniques.
- Publish innovation in research forums.