The Amazon Development Centre in Gdansk is launching its 2019 internship program!
We have positions open across the different teams in Gdansk Development Centre.
Internships will be 3 – 12 months long, running from June 2019, and interns will work closely with a mentor in one of our Alexa teams. By partnering closely with our Software Development Engineers, you have the opportunity to work on cutting-edge technology and contribute to projects which improve products and services for our customers.
The closing date for applications is the end of March 2019, and we will start interviewing in December 2018 until April 2019.
Located in one of the most progressive regions of Poland, the Gdansk Development Center offers exceptional opportunities to grow your technical and non-technical skills by working on exciting and challenging projects.
Teams of developers and researchers work on revolutionizing the way users interact with Amazon products and services. We focus on distributed systems and technologies such as Text-to-Speech and Natural Language Understanding to make a real difference to customers by inventing, enhancing, and building world-class software.
Our work is large-scale and complex, and it demands invention. We offer great opportunities to work on big data, machine learning, and high-scale, low-latency distributed systems.
We’re building the speech and language solutions behind Amazon Alexa and other Amazon products and services.
Our Text-to-Speech team powers Alexa with high quality, natural-sounding voices and delivers numerous voices to Amazon devices.
Cloud Text-to-Speech Services
We create ultra-low-latency cloud services that enable app developers and device producers to integrate high-quality, customizable Text-to-Speech in their solutions with ease.
Natural Language Understanding (NLU)
We are developing natural-language solutions to revolutionize how customers interact with Amazon’s products and services.
Data Pipeline Team (DPT)
We are inventing scalable, data-driven solutions to complex linguistic problems and generating the language data that powers our Spoken Language Understanding (SLU)-based systems.
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