Are you a MS or PhD student interested in a 2021 Applied Science Internship in the fields of Speech, Robotics, 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.
Machine Learning Science:
Amazon has multiple positions available for Machine Learning Scientists in Berlin, Cambridge, Edinburgh, Iasi and Tuebingen.
A few of the teams that are hiring include:
Speech and Language Technology:
We are hiring in all areas of spoken language understanding: ASR, NLP, NLU, Knowledge Graphs, Machine Translation, text-to-speech (TTS), and Dialog Management. Amazon has multiple positions available for Speech Scientists in Aachen, Barcelona, Berlin, Cambridge, Edinburgh, Gdansk, Haifa, Tel Aviv and Turin.
A few of the teams that are hiring currently include:
Amazon has multiple positions available for Computer Vision Scientists in locations such as Berlin, Barcelona, Tuebingen, Haifa and Tel Aviv.
We are currently hiring for multiple teams including:
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