Interactions, LLC is the world?s largest independent AI company. We
operate at the intersection of customer experience and AI ? two of
today?s most innovative and dynamic industries. Since 2004, we?ve
helped leading companies like MetLife, Citi, Shutterfly, and LifeLock
have millions of successful conversations, resulting in saving
operational cost and increasing productivity.
As a member of one of our Technology teams, you will contribute to
building solutions that use natural language processing, cognitive
computing, and artificial intelligence applications or the frameworks
and infrastructure that support them.
The Principal Inventive Scientist is responsible for conducting
original research by developing novel algorithms, implementing them as
software tools, and building models for improving accuracy of
conversational AI technologies. They are expected to participate and
publish their research at technical conferences.
Using data from Interactions? vast human-annotated speech and text
databases develop high-performance models and algorithms, including
acoustic, language, confidence, and intent classification models to
support integration of the results into commercial products.
Responsible for making improvements to speech and language software
and modeling methods and to invent new methods to improve performance.
Work with and advance technology in automatic speech recognition, deep
neural networks, machine learning, acoustic modeling, language
modeling, machine learning, and modeling with unsupervised and
Actively participate with team members to develop innovations that
push the edge of science forward.
Implement new algorithms, format and process large text/audio
databases, run experiments to measure performance, and support
implementation of successful results into products
– PhD or MS with industry experience in computer science, engineering,
linguistics, or a related field.
– At least five years of direct experience.
– A solid understanding of speech and language processing.
– A strong publication record of research through papers and presentations.
– Strong software background in Python, C/C++, and Linux shell.
– Experience in applying deep neural networks (CNNs, RNNs, LSTMs, etc.)
or other deep learning methods to speech recognition or natural
– Experience with speech and language or other machine learning software
such as Kaldi, Pytorch, TensorFlow, or scikit-learn is a plus.
– Familiarity with a non-English language.
– Strong record of collaboration and team-work.