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Behind every great platform, there’s a great team. Our engineers work together to build the future of contextual intelligence in a cooperative, collaborative environment.
We provide our engineers exciting scale and the latest software so they can grow as we do.
We’re pushing ahead on computer vision, NLP and deep learning.
We process 50 terabytes of data every day with a cutting edge tech stack.
Our AWS-hosted Ad Server answers 25 million requests per minute.
Our annual hackathon gives GumGummers complete freedom to come up with their own ideas and work on them with a team of their choice for 48 hours.
The perfect answer for the new remote work reality, engineers built this internal portal during a hackathon. Now, it gives remote employees a way to stay connected by sharing team news, life events, photos and company updates.
Our engineers work with exciting forms of artificial intelligence, including computer vision and natural language processing, to build contextual analysis tools that move the digital media industry forward.
GumGum supports ongoing learning for our engineers by paying for classes and books, sponsoring attendance at conferences and promoting a culture of knowledge sharing.
Engineers at GumGum work on projects that inspire them, from concept through release. You'll have the autonomy to explore solutions to a wide variety of challenges in a supportive environment.
Teaching a machine to categorize something into multiple, non-exclusive groups can feel a little lot juggling...
I think a lot of managers struggle with Delegation. Especially those that are go-getters and initiative takers!...
Nowadays caching is an immensely effective strategy to provide smooth user experience while also greatly reducing resource consumption...
GumGum is doing its part to ensure the web remains an open and welcoming place for all by encouraging diversity in the workplace and community contributions.
GumGum engineers create original open source projects and contribute to others. Learn how we built the GumGum EZ Video Player, then check out our GitHub repositories.
