Beeswax is looking for a Lead Machine Learning Engineer to join our growing team. We were recently recognized on the Inc. 5000 list as #46 in the fastest growing companies and #5 in the top software companies. In 2018, we were also named by Business Insider as the “fastest growing company in AdTech"

Beeswax is an easy to use, massive scale and high availability advertising platform founded by industry veterans who worked together at Google. We’re well funded by leading VCs, such as RRE and Foundry Group, and are rapidly expanding our customer list and our engineering team. We offer our customers the most extensible and transparent advertising platform in the world and process millions of transactions per second.

 Our engineers come from major tech companies such as Amazon and Facebook as well as many other companies with strong software disciplines. We take pride in our mission to build great advertising software.

Our tech stack is constantly evolving to meet the challenges of the massive scale of transactions on which we operate. To manage the firehose of data coming in, we explore complex tradeoffs and carefully architect high performance distributed systems. Those in turn require elegant and thoughtfully designed interfaces to make the systems accessible to both our team and our customers.

We are looking for a Lead Machine Learning Engineer for our Optimization team. The ideal candidate will have experience working on a range of optimization problems in a production environment, such as click-through rate prediction, click-fraud detection, payment fraud, search ranking, text/sentiment classification, viewability prediction, or spam detection.

Your primary role will be to lead and grow a machine learning team to support both internal feature development and the creation of a framework our customers can use.

  • Work with customers and the product team to design optimization systems for both off-the-shelf use and customization through APIs
  • Develop highly scalable machine learning systems to automatically score and optimize real-time bidding advertising campaigns
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore and SMP)
  • Build and iterate on a workflow that enables our customers to take advantage of our data and ML infrastructure
  • A minimum of 5 years experience building ML infrastructure and production models in a product driven driven environment
  • Experience with both batch and stream processing techniques at scale and in cloud platform environments
  • Proficiency with statistics and statistical methods
  • Experience with scripting languages such as Python and shell scripts
  • Experience with big data technologies such as Kinesis, Spark or Snowflake is a plus
  • AdTech experience a plus

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