(apologies for cross-posting)
Hi all,
Thank you,
Zafar
Gracenote is an entertainment data and technology provider powering the world’s top music services, automakers, cable and satellite operators, and consumer electronics companies. At its core, Gracenote helps people find, discover and connect with the entertainment they love. Daily, Gracenote processes 35 billion pieces of data and is quickly becoming a world-leader in return path “big data.” Over the past 3 years, the company has grown to more than 2000 employees in 17 countries, including over 600 of the world’s top engineers with a passion for music, video, sports, and entertainment technology. Founded in 1998, Gracenote is one of America’s most iconic and respected media companies.
We are presently looking for an Audio Research Engineer to join the Applied Research team at Gracenote. This team develops cutting edge technologies relating to music and audio, including media recognition, machine listening, data processing pipelines, and recommendation systems. In your role on the team, you will help develop and disseminate these technologies throughout the company and to customers by developing algorithms and tools, creating demo applications, and writing production system components.
Applicants should include a cover letter.
FOR THIS ROLE WE ARE LOOKING FOR INDIVIDUALS THAT HAVE:
- Practical and theoretical experience with machine learning and digital signal processing
- Experience with neural network based data classification
- Good programming skills in Python, C/C++, and Matlab
- Interested in working on an ever-changing list of audio related projects
- Enthusiastic about audio, music, music data, and solving problems in this space
- Self starter capable of working independently and across a variety of engineering teams
- Masters or PhD in Computer Science, EE, or a related field preferred
DESIRABLE:
- 2+ years of professional experience in neural network based machine learning with audio
- Experience with accelerated machine learning tools such as Tensorflow, Keras, Theano, etc.
- Cross platform experience - Linux, Windows, OS X
- Versatile candidates with experience in a variety of other languages such as Swift, Objective C, Java, _javascript_, Scala, etc.
- Familiarity with music and music technologies (e.g. MIDI, music theory)
- Bash and shell scripting experience
- Experience handling large amounts of data and familiarity with databases
- Experience developing end to end project workflow in Machine learning systems - literature review, data collection, building ML system infrastructure, evaluation systems, and productionizing / integration into services
- Experience building native applications for Mac, Windows, iOS, and Android
- Experience with cloud services such as AWS or Google Cloud
- Experience setting up cloud systems involving the Apache technology stack
Our passion for music, TV, movies, and sports is at the heart of everything we do. But what really makes us tick is our people. From Emeryville to Sydney and Queensbury to Amsterdam, we are building the team that’s going to disrupt the digital universe. This starts by creating a workplace where all things entertainment are celebrated and innovation can come from anyone. If you are interested in being mission critical and on the leading edge of global entertainment technology then please contact us today!
#LI-GN
Gracenote, a Nielsen company, is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or _expression_, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.