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 have positions on the following teams:

Team Name: Personalization
Domain / Research Focus: Recommender Systems / Sequential models, Reinforcement Learning
Team Description: We undertake research to advance the state-of-the art in recommender systems, and we serve personalized recommendations to Amazon customers using the retail website (and app) world-wide. Our work combines machine learning and software development for the full pipeline of data processing/curation, model training, validation and deployment.

Team Name: Recruiting Engine Exploration
Domain / Research Focus: Machine Learning, AIR
Team Description: The Recruiting Engine Exploration teams are a mix of engineers, managers, and scientists who help candidates on their journey to finding the best role for them at Amazon. We are deeply passionate about building tools using the latest technology and share a common interest in scientific methods founded on explainability and algorithmic fairness.

Team Name: Ad Risk
Domain / Research Focus: Customer Trust / Machine learning, Anomaly detection, Pattern Recognition
Team Description: We protect customers worldwide from the risks of malware and fraud ads trafficked through Amazon Advertising. Our automated and transparent systems process millions of transactions daily to prevent, identify and block attacks which exploit customers. We are a multidisciplinary team of developers, scientists and security engineers operating in an adversarial space. We combine disciplines such as machine learning, security engineering, and software development to experiment fast and innovate on behalf of our customers.

BASIC QUALIFICATIONS

· Experience programming in Java, C++, Python or related language
· Master's in Computer Science, Mathematics, Machine Learning, or related quantitative field
· Enrolled in a PhD or Master's degree in Engineering, Computer Science, Machine Learning, Operations Research, Statistics or related fields
· 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

PREFERRED QUALIFICATIONS

· 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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