Lead Product Manager, Embedding & Search

TwelveLabs • San Francisco, CA

2d • $200,000 - $215,000 • Hybrid

About The Position

TwelveLabs is pioneering the development of cutting-edge multimodal foundation models that comprehend videos like humans do. With significant funding and a global presence, we are transforming media interaction and analysis. We value diversity and seek motivated individuals to push the boundaries of technology in video understanding and multimodal AI. This role focuses on Marengo, our multimodal video embedding model, and Search, the product built on it. These are central to our platform, used in production, and are areas of intense competition and complex product decisions. The Lead Product Manager will own both, setting strategy and roadmap, collaborating with research on model development and evaluation, and working with customers and field engineers to address production issues and future needs. The role requires depth in research partnership, customer/field engagement, and internal product execution, covering the full stack from evaluation data to API deployment across various environments.

Requirements

• Research, ML, or engineering background with real work in retrieval, embeddings, vector search, or multimodal models, and a move toward product management
• Experience as a senior solutions engineer or forward deployed engineer with deep ML understanding, acting as de facto product owner on complex customer problems
• Ability to engage deeply on retrieval architecture tradeoffs with researchers and frame product decisions for GTM teams
• Strong opinions about what makes search work in production, backed by evidence
• Strong opinions on how to best serve humans and agents as distinct customer segments
• Ability to see current customer needs and extrapolate future needs, using current demand as a foundation for roadmap decisions
• Shipped product with strong enterprise and PLG (Product Led Growth) motions attached

Nice To Haves

• 5 to 8 years of experience (demonstrated capability is key)
• 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 augmenting product development and releases with modern AI tooling
• Working fluency in English and Korean

Responsibilities

• 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

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed