Amazon
Senior Applied Scientist (L6), Selection Monitoring
Amazon, Indiana, Pennsylvania, us, 15705
Senior Applied Scientist (L6), Selection Monitoring
What does our Selection Monitoring do?
The 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 the 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 and 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, marketplaces, and data sources)You will help us to:Build a scalable system which can algorithmically extract information from the World Wide WebIntelligently cluster web pages, segment and classify regions, extract relevant information, and structure the data available on semi-structured web pagesBuild systems that will use existing knowledge bases to perform open information extraction at scale from visually rich documents.Key Job Responsibilities
- Use AI, NLP, and advances in LLMs/SLMs to create scalable solutions for business problems- Efficiently crawl the 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- Lead projects and mentor other scientists and engineers in the use of ML techniques.BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business applications- Experience programming in Java, C++, Python, or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy, etc.- Experience with large scale distributed systems such as Hadoop, Spark, etc.- Master's degreePosted:
October 4, 2024 (Updated about 3 hours ago)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr
What does our Selection Monitoring do?
The 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 the 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 and 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, marketplaces, and data sources)You will help us to:Build a scalable system which can algorithmically extract information from the World Wide WebIntelligently cluster web pages, segment and classify regions, extract relevant information, and structure the data available on semi-structured web pagesBuild systems that will use existing knowledge bases to perform open information extraction at scale from visually rich documents.Key Job Responsibilities
- Use AI, NLP, and advances in LLMs/SLMs to create scalable solutions for business problems- Efficiently crawl the 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- Lead projects and mentor other scientists and engineers in the use of ML techniques.BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business applications- Experience programming in Java, C++, Python, or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy, etc.- Experience with large scale distributed systems such as Hadoop, Spark, etc.- Master's degreePosted:
October 4, 2024 (Updated about 3 hours ago)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr