DESCRIPTION

What does our Selection Monitoring do?

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 information Extraction, Efficient crawling at internet scale. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and 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 (extreme 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 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 pages
– Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents.

Key job responsibilities
Job Responsibilities
– Use AI, NLP and advances in LLMs/SLMs 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
– 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

BASIC QUALIFICATIONS

– 3+ years of building models for business application experience
– PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience
– Experience programming in Java, C++, Python or related language
– Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

– Experience using Unix/Linux
– Experience in professional software development
– Experience in patents or publications at top-tier peer-reviewed conferences or journals