Airtime is looking for a combined data scientist+engineer reporting to the head of data science who will own building and improving our real-time machine learning and recommendation systems.
Today, online means alone immersed in microblogs and success theater. We're changing that. We are charting the course for the next era of the Internet: live, shared experiences. We're building a new way to use the Internet together.
That’s why we’re pioneering a new kind of social experience, one designed for togetherness. At its core, Airtime is a social platform for doing whatever together. Gather with your people to explore the Internet: group video, listen to music, chat, watch stuff, send pictures, GIFs, and more.
Go watch the app marketing video on https://air.me/ then check out the app in person.
Our company was founded a few years ago by Sean Parker and Shawn Fanning and is backed by Kleiner Perkins, Andreessen Horowitz, Google Ventures, Founders Fund, and a host of other amazing partners.
What You’ll Do
- Work alongside the product, engineering and data science teams to build scalable real-time machine learning and recommendation systems for friends to make, rooms to join, media to watch together, and contacts to invite to Airtime
- Transform a stream of 100k user events per minute into real time recommendation updates for millions of users.
- Work with the backend and data science team to build a system like Uber’s Michelangelo (https://eng.uber.com/michelangelo/) that allows for efficient exploration of different algorithms and approaches.
- Work with multiple data sources including Kinesis, SQS, Aurora, MongoDB
Who You Are
- Motivated to do and learn what is necessary to accomplish your goals: You’ll bring your existing experience to bear but you will need to learn about our product space, engineering environment, and novel ways to meaningfully improve the quality of our recommendation systems.
- Excited by both data engineering and machine learning challenges. It will be necessary to feel comfortable with the entire data science pipeline and engineering environment. You’ll solve theoretical problems and write code at scale.
- Comfortable with, and better yet excited by, product exploration. We are continually changing and improving our product to delight users.
- Have a strong engineering and analytics mindset. You don’t need any particular degree just a provable track record of delivering.
- Works well with a team. Not a cowgirl or cowboy. Teams that encourage and foster debate in a healthy way provably deliver the best work.
- Focused on value add for the user. That means we leverage third-party libraries and tools where it makes sense, but have also been committed to building key technology in-house that sets Airtime apart. You can read more about it on our tech blog at https://techblog.airtime.com/. In short we’ve built a nodejs microservice based messaging backend, globally distributed WebRTC based media stack, Android+iOS mobile clients, and desktop client.
- Similarly, on the data science side we leverage Redshift, Looker, Segment, Mixpanel and whatever else that helps us achieve our goals faster
- Minimizes meetings. We are a distributed team across NYC, SF, and PA but besides our weekly 30 minute sprint planning and company all hands we only have one-off meetings as necessary to discuss specific product or technical topics. We generally just coordinate on Airtime and on Slack.
What Happens Next?
- If you like what you’ve seen and heard then apply!
- After you apply we’ll reach out to discuss to make sure there is a good overall fit.
- If there is a good overall fit, you’ll have some phone chats with our head of data science, VP of Engineering and VP of Product
- If that goes well, we will ask you to complete an analysis and machine learning challenge directly related to what you’ll be doing.
- If that goes well you’ll come on site and talk to around four team members where you’ll go over a variety of data science and engineering topics
- If everything goes well we will be back to you in a day or so with our answer and maybe an offer!
Are you in?