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 interns for the following team in Luxembourg:
Team Name: Network Planning Research Science EU ATS
Doman / Research Focus: Operations Research, Approximation Algorithms & Combinatorial Optimization
Team Description: We design and implement scalable algorithms to solve combinatorial optimisation problems. Example problems are facility location, max coverage, network flows, scheduling, vehicle routing, network design, all with multiple millions of variables and constraints
Team Name: EU GTS Research and Applied Science
Domain/Research Focus: Optimization
Team Description: We solve Volume Allocation, Routing and Scheduling problems for the whole EU network in one single application. This application consists of optimization, simulation and evaluation of the transportation network. We keep on improving the models by researching into new approaches in graph, robust and stochastic optimization.
Team Name: TEN Search
Domain / Research Focus: NLP / Deep Learning / Machine Learning / Information Retrieval / Search AI
Team Description: We undertake research to improve the search results and hence the customer experience on Amazon Stores globally. This combines many disciplines such as machine learning, natural language processing, transfer learning, learning to rank, and software development.
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.
· 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.
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
EU Student Programs Team