ML Research Engineer, Video Cognition System

WHO WE ARE At TwelveLabs, we are pioneering the development of cutting-edge multimodal foundation models that have the ability to comprehend videos just like humans do. Our models have redefined the standards in video-language modeling, empowering us with more intuitive and far-reaching capabilities, and fundamentally transforming the way we interact with and analyze various forms of media. With a $110+ million in Seed and Series A funding, our company is backed by top-tier venture capital firms such as NVIDIA’s NVentures, NEA, Radical Ventures, and Index Ventures, and prominent AI visionaries and founders such as Fei-Fei Li, Silvio Savarese, Alexandr Wang and more. Headquartered in San Francisco, with an influential APAC presence in Seoul, our global footprint underscores our commitment to driving worldwide innovation. Our partnership with NVIDIA and AWS gives us access to the most advanced chips, including B300s, enabling us to push the boundaries of what's possible in video AI. We are a global company that values the uniqueness of each person’s journey. It is the differences in our cultural, educational, and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI. ABOUT THE TEAM The Video Cognition System team is building the world's first video cognition system that transforms raw video archives containing millions of hours of footage into a queryable, structured Video Memory & Cortex accessible to vertical LLM agents. We're tackling foundational questions about what constitutes machine cognition: perception, memory, reasoning, and attention. We design what and how memory should be structured for machines that go beyond the context window, and build the cortex that can reason across an entire archive of videos. Our work spans corpus-level reasoning, knowledge extraction, indexing architectures, tool-based operations, multi-video understanding, and agentic workflows. This requires a close partnership between research and engineering, and we care deeply about building systems that are both scientifically rigorous and practically impactful. Our research team has access to the most advanced chips in the world, including NVIDIA B300s, to push the boundaries of video cognition and understanding systems—accelerating our research-to-production cycle as fast as possible. ABOUT THE ROLE This position spans two tracks—Research Scientist and Research Engineer—determined by your strengths and interests. These roles exist on a spectrum rather than as discrete categories; both contribute to research and implementation. As a Research Scientist, you will explore fundamental questions in video reasoning, retrieval-guided QA, and multimodal understanding, driving research from hypothesis formulation to experiment design and analysis. You’ll investigate how video agents can interpret long-form content, connect evidence across modalities, and deliver reliable, structured outputs that reflect real user needs. As a Research Engineer, you will focus on translating research ideas into robust, scalable systems. You’ll build and optimize pipelines that support indexing, retrieval, and agentic workflows, and develop the infrastructure that accelerates experimentation and ensures our models perform reliably in production. Your work will bridge the gap between exploratory research and the systems that power real-world applications. Both tracks contribute to advancing our video agent capabilities, and both require a balance of curiosity, technical depth, and collaborative problem solving. YOU MIGHT BE A GREAT FIT IF YOU HAVE We’re looking for candidates with research or engineering experience in areas related to video understanding, multimodal retrieval, temporal reasoning, or agent-driven workflows that combine models, tool