Machine Learning Software Engineer

Company: Chomp
Location: San Francisco, CA
Web: www.chomp.com

Chomp is building a social app discovery engine to help people find the apps they need and don't know they need now. We have been gaining significant traction on the iPhone platform since launching in January of this year by combining a unique search and recommendation experience for apps. As the most mature mobile app market, the iPhone and iPod Touch currently nets Apple more than 1 billion app downloads every 60 days. The strategy of the company is to expand to other platforms (Android, iPad, Web-HTML5) and thus build a destination portal for users to discover mobile apps. As apps become an increasingly favorable method with which users consume content on their devices, we believe we're building an important product within the app discovery space that extends to all app platforms.

We're currently applying topic modeling to app meta data to build a better search experience for users finding apps. That is, being able to search for apps by functionality or topic area as opposed to keyword based on the app title or description. Check out our recent press on MobileBeat.

The company is backed by a number of top tier VCs with a small and exceptional team that consists of folks from successful companies such as Google, YouTube and AdMob. We're looking for the early members of our research engineering team to build a team (rivaling that of Aardvark whom Ben Keighran , Chomp CEO advised, and was subsequently acquired by Google early in 2010) to help develop our recommendation and search engine that would allow consumers to discover apps on these various platforms.

Who we're looking for:

Responsibilities:

• Owning design and development of the recommendation engine at Chomp
• Staying aware of state of the art research, using that and the product goals to plan algorithmic improvements and producing production quality code that implements those improvements
• Any other personalization of user facing "home screen" feeds of recommended apps and 'users to follow' that include machine learning
• Ability to work in areas outside of their usual comfort zone and get things done quickly

• Personal engineering projects showing strong engineering aptitude and interest in machine learning (highly favored)
• Experience of implementing machine learning (or recommendation) systems in a large scale environment and scaling such systems (highly desirable)
• Experience of implementing/managing Hadoop clusters (highly favored)
• Strong CS fundamentals with competencies in data structures and algorithms through B.S., M.S. in Computer Science or equivalent qualification/industry experience