Twelve Labs

Research Scientist

• Research multimodal representations that connect temporal and spatial structure with semantic understanding.
• Develop models that operate across multiple levels of granularity, from full videos and clips to regions and entities.
• Design training objectives, datasets, evaluation methods, and large-scale experiments.
• Use task-specific vision models as supervision or components, and integrate useful signals into general-purpose representations.
• Partner with research and engineering teams to scale and ship new capabilities.

Senior ML Research Scientist, Perception Models

AI Engineer

• Design and own developer- and agent-facing surfaces: public and partner APIs, and agent integration interfaces such as MCP and agent-to-agent protocols.
• Build the authentication and authorization substrate: how users and machines authenticate, and how access is enforced (RBAC, organization and team scoping).
• Ship enterprise-readiness capabilities: organization support, per-API-key usage tracking and metering, and rate limiting designed around real system constraints rather than arbitrary defaults.
• Keep the platform reliable and scalable: define and uphold SLOs, harden failure paths, and keep services healthy under real-world and multi-tenant load.
• Move fast without compromising quality, shipping to customers on a tight loop while holding a high craftsmanship bar.
• Collaborate closely with engineering and research partners to turn cutting-edge capabilities into durable product surfaces.

Senior AI Engineer, Tools & Agents

Human Resources

• Partner with technical leaders on org design, workforce planning, and scaling, translating business and product priorities into a clear people strategy
• Guide leaders and teams through growth, restructuring, and other moments of change
• Define how HRBP work functions in Korea - building the playbooks, practices, and feedback loops the People team runs on, and contributing to how global People programs evolve based on what you learn on the ground
• Own talent and performance end to end, from reviews and calibration to promotions, leveling, and succession, setting a high bar for technical talent
• Coach managers and senior leaders, and strengthen a high-performance, high-trust culture and strong employee experience
• Serve as a thought partner to the Country Manager, Korea & Global Head of People on cross-regional people strategy - not just executing global programs in Korea, but shaping how they work across regions
• Partner with the People team across the employee lifecycle and employee relations, keeping practices fair and compliant with Korean labor law
• Use people data and modern tooling to sharpen decisions and improve how People programs run

Senior HR Business Partner, Technical Organizations

Scientist

• 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

Product Scientist, Embeddings – Search

Backend Engineer

• Design and own developer- and agent-facing surfaces: public and partner APIs, and agent integration interfaces
• Build the authentication and authorization substrate
• Ship enterprise-readiness capabilities
• Keep the platform reliable and scalable
• Move fast without compromising quality
• Collaborate closely with engineering and research partners

Senior Backend Software Engineer – Tools & Agents

Engineering Manager

• Own the search system end-to-end (e.g., vector/ANN indexing, lexical retrieval, hybrid fusion, reranking, and temporal (segment-level) search), built on Marengo embeddings and Pegasus and scaled to millions of hours across both ingestion and index creation.
• Design and build the agentic search harness that infers human *and* agent intent and orchestrates multi-turn, session-based (conversational), and parallel search sessions, including subagents that can be invoked by a primary agent.
• Set and own the search-quality bar for both human- and agent-initiated search, and drive continuous improvement against them.
• Own reliability and systems design for the search stack so the system stays dependable as both human and agent traffic grows.
• Drive cross-functional alignment with Research/Training, Platform/Infra, and Product on retrieval strategy, API contracts, and system boundaries.
• Build and lead the team: recruit strong engineers and scientists, set engineering patterns and standards across the search stack, and raise the bar through architecture review, code review, and technical mentorship.

Senior Engineering Manager, Search – Cognition System

Application Engineer

• Unify the internal data and evaluation platform
• Build a secure access layer over very large data
• Bring real customer signal into the loop
• Support the product org's internal agentic content curation

Staff AI Application Engineer, Product

Product Manager

Lead Product Manager, Embedding, Search

Software Engineer

• Build and lead the Partner Engineering team, defining its charter, operating model, and success metrics.
• Develop and execute the global partner engineering strategy across key ecosystems (cloud providers, AI platforms, ISVs, and enterprise integrators).
• Guide technical pre- and post-sales efforts, ensuring seamless partner onboarding, solution design, and integration with Twelve Labs APIs.
• Collaborate cross-functionally with Product, Engineering, and GTM leaders to align on technical roadmaps and market opportunities.
• Run enablement programs for partner technical teams (e.g., cloud solution architects, AI/ML teams) to integrate and scale Twelve Labs technology within their environments.
• Drive co-innovation projects, developing proof-of-concept integrations that demonstrate the value of Twelve Labs technology and inspire broader adoption.
• Represent Twelve Labs externally—speaking at conferences, publishing technical content, and cultivating thought leadership in the AI and video intelligence space.
• Monitor the competitive landscape and emerging technologies to inform product strategy and identify high-leverage opportunities for integration.
• Partner with leadership to shape go-to-market models, pricing structures, and joint business plans with strategic partners.
• Serve as the customer’s technical advocate, synthesizing partner feedback into actionable insights for the product roadmap.