Video is 90% of the world's data. Most of it is invisible to machines.
TwelveLabs builds the intelligence layer to change that. Our multimodal AI models understand video the way humans do — across sight, sound, and motion — and power production-scale AI workloads across media, entertainment, sports, security, and government.
We have raised more than $210 million from NEA, Radical Ventures, Amazon, NVIDIA, Snowflake, Databricks, Index Ventures, NAVER Ventures, Korea Investment Partners, Quadrille Capital, Red Bull Ventures, and AI pioneers including Fei-Fei Li, Silvio Savarese, and Alexandr Wang.
We are a global company, headquartered in San Francisco with offices in Seoul, New York, and London, and employees around the world. We believe the differences in our cultural, educational, and life experiences make our products stronger. Building technology that understands the world in all its complexity requires people who see it from every angle. We are looking for individuals who are driven by hard problems and want their work to matter. Come build it with us!
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 retrieval breaks in production and what they will need six months from now.
Your week splits roughly three ways: research partnership, customer and field work, and internal product execution. The role requires real depth in all three, not fluency in one with awareness of the others.
The scope is the full stack: evaluation data definitions, model evaluation, release cadence and management, ranking quality, the search API, and deployment across managed SaaS, customer hosted environments, and AWS Bedrock. Multimodal video retrieval is becoming an industry assumption. You will be the person deciding how TwelveLabs stays ahead of that curve.
This role is hybrid in San Francisco with two days onsite per week. Due to daily collaboration with our research team in Seoul, we expect availability until approximately 8pm PT on most weekdays, Fridays are an exception.
Set the product strategy and roadmap for Marengo and Search, deciding what gets built, what gets deferred, and what gets killed
Partner with the Marengo research team on model quality: eval rubrics, training data investments, release readiness
Partner with the GTM on launch planning, execution, and enablement including post launch monitoring
Spend real time with customers and field teams understanding where retrieval fails in production and anticipating what they will need next
Define the quality bar for retrieval and hold it across every release and every deployment shape
Own how embeddings and search get deployed across managed SaaS, customer hosted environments, and AWS Bedrock
Stay sharp on the competitive landscape
You have a research, ML, or engineering background with real work in retrieval, embeddings, vector search, or multimodal models, and you moved toward product because you care more about what gets built and why
You have been a senior solutions engineer or forward deployed engineer with deep ML understanding, and you have been the de facto product owner on the hardest customer problems whether or not the title was yours
You can go deep on retrieval architecture tradeoffs with a researcher in the morning and frame a product decision for a GTM team in the afternoon, and both conversations are substantive
You have strong opinions about what makes search work in production and can back them with evidence, not intuition
You have strong opinions on how to best serve humans and agents as distinct customer segments
You see what customers need today and can extrapolate what they will need next. You use current demand as a foundation for roadmap decisions, not just a backlog.
You have shipped product with strong enterprise and PLG (Product Led Growth) motions attached
5 to 8 years of experience, though what matters is demonstrated capability, not tenure
3+ years of shipping products with a model related core
Time at a company where embeddings, vector search, or retrieval was integral to the core product
Experience with multimodal models and the operational cost of running them at scale
Experience in video language models
Experience augment product development and releases with modern AI tooling
A large bonus if you have working fluency in English and Korean
An open and inclusive culture and work environment.
Work closely with a collaborative, mission-driven team on cutting-edge AI technology.
Full health, dental, and vision benefits
️ Extremely flexible PTO and parental leave policy. Office closed the week of Christmas and New Years.