Machine Learning Engineer at AISense
Los Altos, California, United States
🇺🇸 (Posted Jun 2 2018)
About the company
Backed by some of Silicon Valley’s top investors, we are a team of technology industry veterans that are passionate about the future of human-computer interaction and how we accomplish important tasks in our daily lives. We believe the best technologies fit naturally into a user’s daily workflow, and are highly contextual and perfectly personalized for each user’s life. Using our Ambient Voice Intelligence™ technology, developed through our unique approach to speech recognition and deep learning, we are able to understand human-to-human conversations and provide new innovative services. With our extensive history in mobile AI technologies, we are creating the next generation of intelligent and contextually-aware mobile tools to enhance professional productivity. We are proud to be supported by some of Silicon Valley’s top venture capitalists who were early investors in Tesla, SpaceX, Slack, and Twitter. Additionally, we are backed by legendary angel investor David Cheriton, who provided the initial capital to Larry Page and Sergey Brin to start Google.
AISense's main product is Otter: a smart, note-taking and collaboration app that empowers you to remember, search, and share your voice conversations. Try it now on http://otter.ai, Otter - Appstore, and Otter - Google Play.
With Otter, we are adding new life to conversations of all types. Our Ambient Voice Intelligence™ technology processes verbal conversations to derive usable text and identify speakers. It is integrated with a variety of applications. Our direct-to-end user product will change meetings by generating interactive notes that are saved in one place and ready for sharing. Leading unified communications and online collaboration providers partner with AISense to offer transcription, deep content search, summarization, and conversational analytics.
We are seeking an experienced research and engineering professional to lead research and development of new deep learning algorithms for speech recognition and language understanding to join our technology team. Members of the technology team work collaboratively as a group and with colleagues in engineering and product to devise and deploy new algorithms for speech recognition, speaker separation, diarization, and speaker identification.
Skills & requirements
Need to Have:
BS in CS or EECS
Demonstrated familiarity with and understanding of the latest advances in deep learning
Hands on experience with open source deep learning toolkits such as: TensorFlow, Theano, Caffe, Keras
Strong software engineering skills with experience in one or more programming languages C++, Python, and Java
Comfort with working in a highly collaborative startup environment
Nice to Have:
PhD in relevant discipline is highly desirable, but others with equivalent experience are encouraged to apply
Academic specialization or extensive experience in working on solving problems in speech recognition and NLP