So you've acquired a customer; now what?

Marketers have long known that acquiring a customer is not the hardest part — keeping them is. During a relationship with a brand, the customer goes through different lifecycle stages. It's only logical that each stage requires different tactics to keep them engaged. Our platform uses machine learning to predict the lifecycle stage a customer is in and helps marketers automatically deliver the right campaign that captures their attention.

We are growing rapidly and looking for great engineers to join our team.

Our client list is growing, and we're hitting larger and larger amounts of data. We are looking for passionate data engineers to scale out our platform and collaborate with data scientists to implement and improve our machine learning models that crunch billions of data points. Currently, our platform powers thousands of campaigns and processes billions of behavioral signals each day. We’ve sent over a billion individually personalized campaign interactions since our inception!

Like challenging problems? We got you covered.

Our engineers love a challenge. Every day we work with the latest technologies to solve extremely difficult problems involving data, analytics, machine learning, concurrency, scaling, real time stream processing, distributed systems, caching, and more. We optimize every chance we have. For each new challenge, our engineering team focuses on planning up front, prototyping thoroughly yet quickly, then executing with well-tested code. We value simple solutions to difficult problems and have endless thirst to learn learn learn!

We are looking for an experienced data engineer who is passionate about writing clean, well-tested code. You should want to make a huge impact in a fast-paced and cutting-edge start-up environment. You are a spark/scala expert, and you’ll be building robust real-time data pipelines that process billions of events per day and working with our world-class data science team to implement production-quality, scalable machine learning algorithms.

In addition to having meaningful responsibilities and improving engineering chops, you will also receive comprehensive exposure to all aspects of our business. The code and ideas that you contribute will have a tangible impact on the business as a whole. Your code will touch millions of end-users. You will have full responsibility over your projects, and have a real sense of product ownership. You will also have the opportunity to learn tremendously from our awesome team of humble yet super engineers. You'll work with and learn the latest technologies and apply them across our distributed systems.

Our Stack:

We are building the next generation of marketing and data science products, and have a large variety of tools available to us. Our production data stack involves Scala / Spark / Hadoop / Kinesis / Redshift. However, as an engineering team we also make use of Python, Ruby, NodeJS, Java, Dynamo, Mongo, Redis, Flume, Elasticsearch, and whatever the job requires.


  • 3 to 5 years experience working on production data products in Scala or similar
  • You are a Hadoop expert, and also have 1+ years experience with Scala / Spark
  • Proficient in at least one statically typed language
  • Like functional programming
  • Experience designing and implementing large, scalable services
  • Passionate about enforcing software engineering principles, production code quality, and regular use of design patterns
  • Experience interfacing with APIs - SOAP, REST, etc.
  • Experience creating robust RESTful APIs
  • Comfortable using Git, Bitbucket/Github
  • Strong belief that tests and code go hand-in-hand
  • Deep understanding of SQL, query optimizations, joins etc.
  • Excellent CS foundation: data structures, time complexities, algorithms, etc.
  • Startup work experience a major plus!

About Us:

We’ve been named in CRN’s Top 10 Big Data Startups of the Year, Fast Company’s “Innovation Agents” of 2013, SocialTech’s Top 10 Software Company in Southern California, and one of Fox News LA’s most promising startups to watch. Our founders have received awards like the Ernst & Young Entrepreneur of the Year. We come from schools like Berkeley, Caltech, Carnegie Mellon, Stanford, and Yale. We’ve been featured in the Wall Street Journal, Forbes, Entrepreneur, Inc. Magazine, TechCrunch, Bloomberg, and Reuters, among other notable publications.

Our powerful profiling engine uses machine learning techniques and statistical models to analyze purchasing trends based on massive data sets, which we then use to predict customers' behavior and maximize customer retention for our clients. We love creative brainstorming for solutions and the pursuit of innovation-fueled knowledge.

We also like long walks on the beach, the crackle of turning Rubik's cubes, and dogs with old-soul eyes. Because who doesn't?

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Confirmed 52 minutes ago. Posted 30+ days ago.

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