Senior ML Research Engineer, Marengo

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 This team owns the research and development of Marengo, TwelveLabs’ multimodal embedding model. We develop foundation models that bring video, audio, and text into a shared embedding space, powering state-of-the-art multimodal understanding and retrieval. End-to-end model development: We work across a broad range of research areas, including contrastive learning, temporal video understanding, and multimodal representation learning. The team owns the entire model development lifecycle—from building large-scale training datasets and designing model architectures to optimizing distributed training and developing robust evaluation frameworks. Research at scale: With access to world-class compute infrastructure, including NVIDIA B300 GPUs, we rapidly iterate on large-scale experiments, enabling fast progress on ambitious research problems. Research with real-world impact: The path from research to production is exceptionally short. We work closely with the Search, Product, and Infrastructure teams to continuously improve the models that power multimodal search and understanding for thousands of customers worldwide. ABOUT THE ROLE As a Senior ML Research Engineer on the Marengo team, you will drive the research and development of TwelveLabs' multimodal embedding models, from data strategy and training pipeline optimization to model architecture experimentation and evaluation. This is a research-heavy engineering role at the intersection of multimodal representation learning, large-scale distributed training, and data engineering. We're looking for a strong engineer-researcher who can take well-scoped research problems with moderate ambiguity, design rigorous experiments, and deliver reproducible results that ship to production. IN THIS ROLE, YOU WILL - Design and execute experiments to improve multimodal embedding model quality, spanning model architecture, training methodology, data composition, and evaluation - Build and optimize large-scale distributed training pipelines (multi-node, multi-GPU) for contrastive and representation learning - Develop and improve data curation, filtering, and quality assessment pipelines at scale - Conduct ablation studies to systematically evaluate design choices and communicate findings to guide technical direction - Implement evaluation frameworks and benchmarks that rigorously measure embedding model quality - Collaborate with the search/serving team to ensure model improvements translate to end-to-end retrieval quality gains Even if you don't check every box, we encourage you to apply. If