Applied Scientist

Job ID: 803520 | Amazon.com Services, Inc.

DESCRIPTION

Interested to help us building new speech and language technology for Amazon Web Services?

Amazon is looking for a passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading human language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Machine Translation (MT), Text-To-Speech (TTS), and Machine Learning (ML).

As member of our AI team at Amazon AWS, you will work alongside internationally recognized experts to develop novel deep learning models to advance the state-of-the-art in speech and text translation systems. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in speech and text translation. You will be responsible for providing leadership and mentorship to others within the Amazon AI Science teams.

We are hiring in all areas of human language technology, with special focus on Deep Learning (DL) models for speech recognition, machine translation and text-to-speech.

BASIC QUALIFICATIONS

· Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, Mathematics or Physics with specialization in natural language processing or machine learning.
· Comprehensive and deep knowledge of a relevant field of research, such as ML and NLP.
· Solid programming skills.
· Experience using Unix/Linux.
· Good written and oral communication skills (English).

PREFERRED QUALIFICATIONS

· Experience in developing neural ASR, MT, or TTS systems (research or commercial).
· Solid ML background and familiarity with standard DL-based MT/ASR/TTS and ML techniques.
· Scientific thinking and ability to invent, a track record of contributions that have advanced the field.
· Solid software development experience with DL frameworks (MXNET, TensorFlow, PyTorch, etc.)
· Proven proficiency in programming with Python, Java, or C++