Senior Research Machine learning Eng, App Science Infrastructure

Amobee   •  

Redwood City, CA

Industry: Telecommunications


Not Specified years

Posted 30 days ago

Are you passionate about working on everything from hadoop to distributed real-time systems to data mining, machine learning and statistics? Are you excited about building scalable scoring and ranking systems that invoke applied science models for bid optimization a few million times per second? Are you all up for using data science to gain insights and train models over multi-petabyte data warehouses? Are you a brilliant, self-starter who is not satisfied simply with ideas to problems, but are itching to implement the solutions and see them live in production systems? Are you interested in doing part science and part systems? If your answers are yes, then you are the person we’re looking for.

The Research Engineering positions in Amobee’s Platform Applied Science Infrastructure team is a hands on role that contributes to Amobee’s success through expertise in both large-scale systems and applied science. You will leverage hadoop and distributed systems ecosystem to create the next generation of architecture, specifically for applied science. Qualified individuals will have a solid background in the fundamentals of computer science, some expertise in distributed computing and some experience with machine learning, data mining and statistics.

Because we are a small team, your ability to communicate technical ideas effectively, in oral and written forms, and solve complex problems in a team environment will also be considered.


  • Build scalable real-time Ad scoring and ranking systems for bid optimization
  • Design and Develop algorithms and systems for other ‘intelligent’ components in Amobee platform such as budget optimization, multi-touch attribution, campaign diagnosis, A/B testing, PMML infrastructure, science dashboard and advisories
  • Perform data and predictive analytics tasks
  • Use hadoop and other technologies to train models and generate insights
  • Collaborate with other development teams, product management, marketing science, QA, support, operations and customer success teams to deliver new features and improvements to our technology and business
  • Occasionally help troubleshoot production and customer issues

Required Qualifications:

  • A degree in Computer Science at any level is a must. MS/PhD preferred
  • 0-5+ years of relevant experience (appropriate MS/PhD project work acceptable)
  • Experience with Java preferred; other primary languages like C, C++, python acceptable
  • Basic knowledge of and strong interest in machine learning, data mining and statistics is a must
  • Working knowledge of hadoop and relational/non-relational databases preferred
  • Experience with some system design preferred
  • Experience with Linux based operating systems is a plus
  • Must be talented, hard working, self-motivated, humble and cooperative