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Are you a MS or PhD student interested in a 2022 Applied Science Internship in the field of Computer Vision, or Machine Learning/Deep Learning? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful...

Are you a MS or PhD student interested in a 2022 Applied Science Internship in the field of Computer Vision, or Machine Learning/Deep Learning?
Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way?
If this describes you, come join our research teams at Amazon. As an Applied Science Intern, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept.
We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

We are hiring for the following teams in Barcelona:
Team Name: Amazon Search Relevance
Domain/Research Focus: Information Retrieval, Statistics, Natural Language Understanding
Team Description: The Amazon Search Relevance team owns ranking relevant results when customers search for products on Amazon. Our systems and algorithms operate on one of the world's largest product catalogs, surfacing the right products - with a high relevance bar and strict latency constraints. We are looking for Applied Scientists who are excited to improve the search results for hundreds of millions of Amazon customers around the world by developing innovative machine learning-based solutions for hard business and science problems in Search Ranking. We focus on research in Information Retrieval, ML modeling and programming. You will work with the largest online retail search application in the world, both in terms of users and catalogue size. You will have the opportunity to leverage vast AWS computing resources and build solutions to directly improve the experience for millions of our customers.
Team Name: yhat (EU AS APP)
Domain / Research Focus: Time series forecasting, predictive models, decision making
Team description: We leverage Machine Learning to support the Transportation services. Our problems include forecasting the flows of packages in Amazon’s global network, detecting anomalies in time series data, reinforcement learning to make real time decisions and natural language processing to streamline access and exploration of business metrics.

Team Name: Subjective-NLP
Domain /Research Focus: Natural Language Processing for text understanding and information extraction, Deep Neural Networks, Search Applications.
Team Description: we are a science team located in Barcelona, which belongs to the Search Science and Artificial Intelligence (SSAI) organization. We are Applied Scientists experts on Natural Language Processing and Machine Learning, and Software Developers working on improving shopping experiences through understanding subjective customer inputs and feedback (e.g., customer reviews and opinions, Q&As, search queries, etc.). We create state-of-the-art natural language processing algorithms that extract, model and summarize that information, and develop innovative services to improve the shopping experiences of our customers, to help them buy with more confidence and ease.


· Enrolled in a PhD or Master's degree in Engineering, Computer Science, Machine Learning, Operations Research, Statistics or related fields
· Experience in Java, C++, SQL, R, MATLAB, Python, or similar scripting and programming languages
· Experience in design of experiments, statistical analysis, implementing algorithms in computer vision using both toolkits and self-developed code
· Experience in solving business problems through machine learning, data mining and statistical algorithms


· Familiar with the core undergraduate curriculum of computer science.
· Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members.
· Publications at top-tier peer-reviewed conferences or journals.
· Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.

This is not a remote internship opportunity.

Equal Opportunities:
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.
Applicants who apply for this job will allow Amazon to process your application in a centralized hiring system that considers you for other similar openings as well

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