Wetpaint is looking for an energetic, passionate, experienced engineer to join our talented software development team. We have multiple openings available and are eager to add mid-career to senior engineers to speed up our growth. You will become part of a next-generation media and technology startup with a culture of continuous revolution. In 24 months, we built a media property with over 15 million monthly readers, growing twice as fast as Huffington Post in their early days. We earned the trust of over seven million engaged Facebook fans. Today, Wetpaint gets more social traffic than the New York Times, MTV, and Washington Post. Wetpaint is one of the top 100 best places to work in Seattle according to Seattle Business Magazine.
The main enabler behind that is our world class technology infrastructure, which is comprised of complex systems that can spot emergent trends before they are picked up anywhere else, handicap content for the amount of traffic it will drive, and figure out where, when and how to best merchandise this content across channels – web, mobile, and social. At the heart of these systems, which we refer to as our Platform, is a core focus on using data collection, analytics, machine learning, and optimization techniques on data from a variety of sources.
What your typical day may look like…
- Come in around 9 for the daily standup. Find out that one of the other devs has a code review ready and needs someone to take a look. You volunteer to help them.
- By 10:00, you’re done with the code review — you sent them the feedback through Github.
- At 10:05, you look through items for the sprint and begin working on the next one: The audience development team has requested that the system estimate the number of posts it would take to achieve needed power for a certain class of experiments on Facebook. You dig through some math references and whip up a prototype that is based on the normal distribution. At the same time, you send your findings to the in-house statistician to confirm the numbers.
- At 12:30, a few of your colleagues are heading out to grab a sandwich nearby and you join them. You tell them about the model you’ve been building; one of them mentions that their friend did something similar, and found that the formula you’ve been using does not work well for non-normal distribution of data.
- You are back from lunch and you meet briefly with the statistician. He explains to you that there is a better formula to estimate needed power for cases when the data is not distributed normally. The two of you spend a few minutes applying the new formula manually to past experiments and find out that it indeed works. You go back and finish the implementation with the new formula. You add tests to the middle-tier components and you use memcached to aggressively cache calculation results — they won’t change for a while. At the same time, you realize that the system can now end the experiments automatically once estimated number of posts has been published. You send a note to the team to consider including this feature into the system for the next sprint.
- Around 4, you look at Google Analytics and Facebook Insights stats for the component you released a few days ago; you see an unexpected trend — the conversion rate is far higher than you anticipated. You grab a couple screenshots and send a note to the team, encouraging everyone to consider investing into this feature area heavily for the sprint that starts next week.
- You finish the day looking at a data inconsistency issue. It’s surprisingly non-trivial — Facebook Insights sometimes returns null data — so you want to add a few unit tests to make sure it’s covered in the next regression run. You don’t know how to get the fixtures to work quite right; your neighbor has done this before, so he saves you a bunch of time with a few simple answers.
- Around 6, the crew is wrapping up; several folks are beginning a Starcraft match. You use your nerf gun to communicate that their loud screams aren’t helping you write unit tests. A few minutes later, you give in to the temptation and join them.
What you’ll do…
- Scale a Rails application to deliver highly personalized content to a large number of users
- Design and deliver cutting-edge platform applications and web services from DB schema up to the UI
- Use social media API’s to better connect our sites to our users
- Write fault-tolerant data collection systems against external web services
- Analyze and identify data patterns and derive insights in near real-time
- Work with nice, smart people on a young and rapidly growing system
- Be part of an agile team that is obsessively results-focused and values autonomy, mastery and purpose
Skills and Experience
- Successful history of professional Ruby On Rails or Java development
- Experience writing well-designed, performant, high-traffic, customer-facing web applications or services
- Experience collecting and mining large data-sets on a distributed system
- Exposure to Linux, JRuby, Postgres, Hibernate, MySQL, Lucene, Hadoop, Map-Reduce, Elasticsearch
- Versatile self-starter with an eye for detail and a strong sense of ownership
- Generalist: someone who constantly learns new technologies to find the best tool for the current task
- Have a github account with an interesting project on it
To apply, send your resume to email@example.com with “Software Engineer” in the subject line.