Twelve Labs
Technology
LeadProductManager,Embedding&Search
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Product Manager, Embedding & Search at Twelve Labs. Skills: Product strategy, Roadmap, Marengo, Search. Set product strategy for Marengo. Set product strategy for Search”
Industry & Context.
Product decision framing; Retrieval architecture tradeoffs
Availability until 8pm PT, Two days onsite per week
What They're Looking For.
Must Have
Research background, ML background, Engineering background, Retrieval experience, Embeddings experience, Vector search experience, Multimodal models experience, Senior solutions engineer experience, Forward deployed engineer experience, Deep ML understanding, Product owner experience, Search production experience, Serve humans and agents, Shipped enterprise product, Shipped PLG product
Nice to Have
5 to 8 years experience, 3+ years shipping products, Embeddings integral to product, Vector search integral to product, Retrieval integral to product, Multimodal models experience, Video language models experience, Augment product development with AI tooling, Augment product releases with AI tooling, Working fluency in English, Working fluency in Korean
What You'll Do.
Set product strategy for Marengo
Set product strategy for Search
Set roadmap for Marengo
Set roadmap for Search
Decide what gets built
Decide what gets deferred
Decide what gets killed
Partner with research team on model quality
Partner with research team on eval rubrics
Partner with research team on training data investments
Partner with research team on release readiness
Partner with GTM on launch planning
Partner with GTM on launch execution
Partner with GTM on launch enablement
Monitor post launch performance
Spend time with customers
Spend time with field teams
Understand retrieval failures
Anticipate customer needs
Define quality bar for retrieval
Hold quality bar across releases
Hold quality bar across deployments
Own embedding deployment
Own search deployment
Stay sharp on competitive landscape
How You'll Work.
Team & Collaboration
Research team partnership; GTM partnership; Customer collaboration; Field team collaboration
Process & Methodology
Roadmap planning, Release management
Full Job Description
WHO WE ARE At Twelve Labs, 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 remarkable $107 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. 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 ROLE Video is the richest and most complex data type in the world. TwelveLabs builds the foundation models and products that give machines genuine understanding of what is happening inside it. Marengo is our multimodal video embedding model. Search is the product built on top of it. They are the technical center of the platform: what customers deploy in production, what competitors are trying to replicate, and where some of the hardest product decisions live. You will own both. You set the strategy and roadmap for Marengo and Search. You work with the research team on what the model should learn, how to evaluate it, and when it is ready to ship. You work with customers and field engineers to understand where retrie
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