Hooked is using machine learning to disrupt Hollywood. We’re redefining entertainment for teens and millennial with 40M monthly users. We’ve raised funding top investors in Silicon Valley and Hollywood, including Greylock, SV Angel, Cowboy Ventures, William Morris Endeavor, Sound Ventures (Ashton Kutcher), Greg Silverman (ex-President of Warner Bros), Charles King, Snoop Dogg, Jamie Foxx, Mariah Carey, Stephen Curry, Andre Iguodala, Kevin Durant and others. We’re building the media company of the future - the next Netflix, the next Disney.
Android Engineer East Bay, San Francisco, Silicon Valley, or Remote
Machine Learning Engineer East Bay, San Francisco, Silicon Valley, or Remote
Senior Backend Engineer San Francisco or Remote
Senior Fullstack Engineer East Bay, San Francisco, Silicon Valley, or Remote
Growth — We’ve pioneered a new media format called chat fiction, which has become a phenomenon among teens and millennials. Hooked has reached 50MM readers in the past year and has hit the #1 spot in the App Store in 25 countries, including the U.S., U.K., France, Germany, Italy, Japan, and S. Korea. We’re building the media company of the future - the next Netflix, the next Disney. Hooked is already profitable and has consistently been a top 100 grossing app.
Some recent press about Hooked: https://www.thetimes.co.uk/article/the-app-that-has-younger-readers-hooked-dcw67m837 https://www.nytimes.com/2016/12/28/technology/personaltech/text-messaging-takes-more-apps-into-a-chattier-realm.html
Team — We sold our last startup, Khush, to Smule in 2011. As Chief Product Officer and Chief Scientist at Smule, we developed and managed AI-powered mobile apps that have reached over 350M people and $100M in annual revenue. We've produced viral videos reaching over 300M views. Prerna has been named one of the Most Influential Women in Tech by FastCompany, and Parag's machine learning research has been funded by the National Science Foundation, including an NSF CAREER award.
A bit about our founders and the journey that led to Hooked: https://www.vogue.com/article/prerna-gupta-songify-got-rid-of-possessions-lived-as-nomad
Top Investors — Hooked has raised $15 million in funding. We're backed by top investors in Silicon Valley and Hollywood, including SV Angel, Greylock, Founders Fund, Cowboy Ventures, William Morris Endeavor, Sound Ventures (Ashton Kutcher), Kevin Spacey, Greg Silverman (ex-President of Warner Bros), Charles King (Oprah's former agent) and The Chernin Group, among many others.
Opportunity — This is an opportunity for you to join a high-growth, venture-backed startup in the early days and be a core part of the founding team.
Culture — A note about how we work. We are a small team with a huge footprint. This is only possible because we all share an intrinsic motivation to crack the code on mobile storytelling. At the same time, this is a fundamentally creative pursuit. It’s not about grinding out hours unproductively; it’s about finding the mental space and time to have true breakthroughs. We strongly believe in work-life balance. People are at their most productive and creative when they are well-rested and in control of their own schedule. For this reason, we primarily work remotely. We have an office in the Mission district of SF where we meet a couple of times a week. Of course, certain things are best done in person. In sum, how and when you work is largely up to you. We each have our own style; we’re sure you do too. You can read more about our CEO’s philosophy on remote work in this article she wrote for the New York Times:
Our team is friendly and collaborative. We typically start by discussing overall objectives for the next several weeks. We then brainstorm and design specific features or projects. Depending on the nature of the task, this might include discussing with the Lead Product Manager and Designer. In other cases, the discussion might be with the CTO and Lead Engineer. After the design phase, the task will be ticketed. We use Pivotal tracker for this. You will then work on your own to prioritize and implement your tasks, with periodic check-ins with other members of the team. We empower engineers to take ownership and responsibility of their work. We’re a small team of individual contributors. You will push work to production that will impact tens of millions of users.
Hooked reaches over 50 million readers a month. With this scale comes many interesting scaling challenges, from the design of the application server and APIs that support our mobile clients, to the optimization of database schemas and queries.
Hooked processes hundred of millions of data points — every time a user taps to read a message, we collect this information. This gives us unprecedented insight into which stories are working and which are not, as well as potential problems areas. These insights are used to drive our entire content development process. As we continue to grow, how do we efficiently scale these data pipelines and use them to create data visualizations that clearly and efficiently communicate to our content team?
As the number of stories in the app grows, as well as the diversity of our user base, it becomes increasingly important to provide personalized recommendations to our readers. How can this be done at scale? How do we create a system where we can a/b test different recommendation algorithms?
Create a recommendation system that provides personalized recommendations to users by leveraging the data generated by hundreds-of-millions of stories being read. The system must be fast, scalable and support testing different candidate recommendation algorithms.
Create a real-time analytics platform that allows us to visualize the survival curves (how readers get) for each story. This would be segmentable by various attributes such as date, country, platform, and various other user attributes. It would need to be able to handle hundreds of millions to a few billion data points.
For our top stories we work with actors to create audio versions of our story. For the rest of the catalog we have experimented with text-to-speech systems but have found the results more comical than convincing. Build open state-of-the-art TTS systems (wavenet etc) to create TTS system that takes into account the semantic context for the line. What emotion needs to be conveyed? Can we condition on this to guide the TTS system?
We're a warm, friendly, positive group of people. The company has a family-vibe. We love what we do and have complete trust and faith in our team. We are intrinsically motivated to crack the code on mobile storytelling and all the challenges that come with such an ambitious goal. We are highly efficient and prioritize work-life balance. We love the excitement of startup life — of building quickly, testing and iterating, and continuously improving. We love the close connection we have with our millions of users. There's nothing better than the thrill of a consumer entertainment startup.
Interested in this company?
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