Machine Learning Applied Science Intern
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Job Description
About the Company:
Amazon is on a mission to revolutionize information access. Their Applied Science team is at the forefront, developing cutting-edge AI solutions, particularly in recommender systems and information retrieval. They are seeking interns to contribute to these efforts, impacting millions of customers worldwide.
Detailed Job Description:
This Applied Science Internship focuses on Recommender Systems and Information Retrieval within Machine Learning. Interns will work alongside experienced scientists and engineers, tackling complex challenges using deep learning, natural language processing, and large-scale distributed systems.
Key Responsibilities:
• Algorithm Development and Evaluation: Design, implement, and experimentally evaluate new recommendation and search algorithms using large-scale datasets.
• Data Pipeline Development: Develop scalable data processing pipelines to ingest, clean, and prepare data for model training. This involves handling diverse data sources.
• Research and Innovation: Conduct research into the latest advancements in recommender systems, information retrieval, and related machine learning domains.
• Cross-functional Collaboration: Work with various teams to integrate solutions into production systems.
• Communication and Dissemination: Communicate findings through presentations, documentation, and potentially publications.
Specific Areas of Expertise (Preferred):
The company is particularly interested in candidates with expertise in: Knowledge Graphs and Extraction, Programming/Scripting Languages, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Neural Networks/GNNs, Large Language Models, Data Structures and Algorithms, Graph Modeling, Collaborative Filtering, Learning to Rank, and Recommender Systems. The role also involves developing frameworks and tools to streamline the machine learning lifecycle, focusing on knowledge management within ML. This includes researching best practices in ML operations, knowledge engineering, and information management.
Ideal Candidate Profile:
The ideal candidate is a collaborative problem-solver comfortable with ambiguity, possessing strong attention to detail and the ability to thrive in a fast-paced environment. They should be self-starters.
A Day in the Life:
A typical day might involve designing algorithms, implementing them, evaluating their performance, developing data pipelines, conducting research, collaborating with other teams, and presenting findings.
Basic Qualifications:
• Enrolled in a PhD program.
• 18 years of age or older.
• Ability to work 40 hours/week minimum for a 12-week internship maximum.
• Ability to relocate to the internship location.
• Programming experience in Java, C++, Python, or a related language.
• Experience with at least one of the preferred expertise areas listed above.
Preferred Qualifications:
• Publications at top-tier conferences or journals.
• Experience building machine learning models or developing algorithms for business applications.
• Experience with deep learning frameworks like MxNet and TensorFlow.
Locations: Amazon has internship positions available in Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; and Seattle, WA (and potentially other locations).
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.
