SoundHound is creating & productizing transformative technologies that improve life. Join us.
After amassing a global user community well over300 million strong, a large portfolio of core technologies & award winning productswere just getting started.
At SoundHound we value creativity, innovation, hard work, open communication & fast iteration, which allow us to act on valuable feedback from employees & users alike. SoundHound's culture is one of impromptu coffee breaks, less-impromptu fitness sessions, group lunches, & weekly happy hours.
We offer a competitive salary, SoundHound stock options, unique camaraderie, catered lunches, & the opportunity to call a company thats simultaneously changing the way we discover music AND interact with machines, home. Yep, it's that cool.
About the Role:
At SoundHound, we view our data & our engineering team as two of our biggest assets. This rolelives at the intersection of the two.We have a huge amount of data from hundreds of millions of users of:
SoundHound: musicapp featuring search, discovery, & play with LiveLyrics
Hound: newlyreleased app featuring unprecedented speech recognition & natural languageunderstanding
Houndify: platformenabling developers to add voice enabled conversational interface toanything
We aspire to leverage this data to make informed decisions to steer product development, marketingand user engagement. We have only scratched the surface of the kind of advanced analytics andinsight generation we'd like to do! This is an opportunity to work on interesting data engineering anddata science problems, build large scale distributed machine learningsystems from the ground up, anduse cutting edge Big Data technologies like Spark, Kafka, HBase & Hive.
Design & implement data pipelines empowering real timeinsights.
Leverage massive datasets for modeling, recommendations, & reporting solutions.
Build user-facingscalable systems powering ad targeting, push and/or in app
Drive framework for A/B tests, exposing the results through visualization tools like Tableau.
Strong coding skills preferably in Java, Scala, or Python.
Hands-onexperience with large scale Big Data environments (Spark, Kafka, Hive, Hadoop)
Ability to handle multiple competing priorities in a fast-pacedenvironment.
BS/MS in Computer Science or equivalent.
Nice to Haves:
Familiarity with NoSQL stores including HBase/Cassandra, Redis, Riak, and/or Mongo.
Familiarity with data modeling, machine learning, frameworks like Spark MLlib.
Experience with analytical tools supporting data analysis & reporting (eg. Tableau)