Machine Learning Applied Science Intern
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Job Description
About the Company:
Amazon is a global technology company focused on e-commerce, cloud computing, digital streaming, and artificial intelligence. They are on a mission to revolutionize how the world uses machine learning.
Job Description:
This is an Applied Science Internship focused on Information and Knowledge Management in Machine Learning at Amazon. The intern will play a crucial role in developing systems and frameworks that power Amazon’s machine learning capabilities. The work will center around creating intuitive tools and workflows to help machine learning teams discover, reuse, and build upon existing models and datasets, accelerating company-wide innovation. This involves leveraging natural language processing and information retrieval techniques to extract insights from large amounts of unstructured data.
Key Responsibilities:
• Develop scalable, efficient, and automated processes for large-scale data analysis, model development, validation, and implementation.
• Design, develop, and evaluate highly innovative ML models to solve complex business problems.
• Research and apply the latest ML techniques and best practices from academia and industry.
• Focus on improving the customer experience.
• Utilize analytical techniques to create scalable solutions for business problems.
• Collaborate with diverse groups and cross-functional teams to solve complex problems.
• Conduct groundbreaking research into best practices and innovations in ML operations, knowledge engineering, and information management.
• Propose novel approaches to enhance Amazon’s machine learning capabilities.
Required Skills and Experience:
• Enrolled in a PhD program.
• At least 18 years old.
• Ability to work 40 hours/week minimum for a 12-week internship maximum.
• Ability to relocate to one of the internship locations (Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA).
• Programming experience in Java, C++, Python, or a related language.
• Experience with at least one of the following: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Programming/Scripting Languages.
Preferred Qualifications:
• Publications at top-tier peer-reviewed conferences or journals.
• Experience building machine learning models or developing algorithms for business applications.
• Experience with deep learning frameworks like MxNet and TensorFlow.
Compensation: The base pay ranges from $65.38/hr to $107.40/hr, depending on location. Additional compensation may include equity, sign-on payments, and benefits.
