About the job
Join Our Innovative Team
At Twelve Labs, we are on a mission to set global standards in AI for video understanding! Our cutting-edge technology processes vast amounts of video data, enabling specialized features such as search, analysis, summarization, and insights generation through our world-class video-focused AI models.
In collaboration with the largest sports leagues globally, our models swiftly and accurately identify highlights from extensive game footage, delivering a hyper-personalized viewing experience. Our technology is also utilized by national integrated control centers for effective surveillance response using CCTV footage, while major broadcasters and studios around the world leverage Twelve Labs models for content production aimed at billions of viewers.
With offices in San Francisco and Seoul, Twelve Labs is a Deep Tech startup recognized by CB Insights as one of the top 100 AI startups for four consecutive years. We have secured over $110 million in funding from prestigious investors such as NVIDIA, NEA, Index Ventures, Databricks, and Snowflake. Our AI model, developed in Korea, is uniquely available through Amazon Bedrock. Join us as we collaborate with exceptional colleagues to create innovative products and grow alongside our global clientele.
Our core values are:
A commitment to honesty and introspection about ourselves and our teams.
Resilience and humility in the face of failure and feedback.
A dedication to continuous learning and enhancing team capabilities together.
If you relish the journey of solving challenging problems and growing together, this opportunity at Twelve Labs is for you!
About Our Team
The Twelve Labs Machine Learning Engineering (MLE) team is a global group comprising members from both the U.S. and South Korea. We collaborate closely based on mutual respect and open feedback, playing a pivotal role in ensuring that research outcomes translate into real user value.
The MLE team is responsible for the end-to-end implementation and operation that connects internally developed AI models to actual products. We participate in the entire lifecycle from model training to serving, designing systems that utilize large-scale GPU resources effectively (B300, H100, L40s, etc.). Additionally, we build data pipelines and platforms to reliably handle large-scale video data, laying the groundwork for rapid experimentation and iteration.
Our MLE team directly engages in internal model training processes, continuously improving the development cycle to expedite the transition of research findings into products. By consistently incorporating user experience and actual needs into model development, we foster a virtuous cycle of growth for both products and models.
In an environment where uncertainty and technical challenges are the norm, we face problems without predetermined solutions. Each time, we learn quickly, experiment boldly, and collaboratively devise solutions most suitable for the goals of the Twelve Labs team and product.