Twelve Labs

Product Manager

• 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

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.

Director of Partner Engineering

Solutions Engineer

• Deliver an exceptional customer experience by providing technical expertise, scoping use cases, and supporting the implementation of video AI applications with technical stakeholders at startups and enterprises.
• Own technical relationships with strategic customers, ensuring successful integrations, resolving complex technical challenges, and driving adoption across their organizations.
• Guide customers on best practices for leveraging TwelveLabs APIs to create secure, scalable, and differentiated video understanding experiences.
• Serve as the first line of defense for design, security, compliance, and architecture questions, escalating complex requirements to internal experts as needed.
• Create and maintain documentation, implementation guides, and FAQs for common customer requirements and technical challenges.
• Gather customer feedback and represent the voice of developers and enterprises to internal teams, helping shape product roadmaps and future capabilities.

Solutions Architect

Machine Learning Engineer

• Pegasus 내 학습 인프라 및 학습 운영의 기술 방향을 주도하면서, 핵심 시스템 설계 및 구현에 직접 깊이 참여합니다.
• 대규모 분산 환경에서의 안정성, 재현성, 효율성, 빠른 반복 실험을 핵심 가치로 삼아 확장 가능한 End-to-End 학습 파이프라인의 설계와 고도화를 총괄합니다.
• 멀티모달 모델 개발을 위한 데이터 큐레이션 워크플로우, 학습 시스템, 평가 파이프라인, ML 인프라 전반의 기술적 의사결정을 주도합니다.
• 리서치 아이디어가 견고한 시스템으로 신속하고 안정적으로 전환되어 프로덕션 모델 개발에 통합될 수 있도록, End-to-End 학습 라이프사이클을 개선하고 자동화합니다.
• 탁월한 기술적 판단력을 바탕으로 설계 리뷰와 실무 협업을 통해 엔지니어를 멘토링하고 팀 전체의 실행력을 높입니다.
• Claude, Gemini, GPT 등 AI 기반 개발 도구를 적극 탐색·도입하여 코딩, 실험, 디버깅, 문서화 등 전반에 걸친 생산성을 향상시킵니다.

Staff Machine Learning Engineer – TrainingOps

Account Manager

• Collaborate with Product, Marketing, and Tech teams to plan and produce press releases and in-depth feature stories
• Own PR strategy and manage Korea communication channels to maximize brand visibility
• Drive agenda-based media outreach and measure coverage outcomes
• Design executive interview scripts and media engagement strategies
• Develop content across formats: written articles, interview scripts, video storyboards, and presentation materials
• Build and maintain relationships across Korea's public sector — government ministries, public agencies, and industry associations
• Surface relevant meetings, events, and conversations, and connect them to internal teams as actionable opportunities
• Monitor policy trends, procurement cycles, and competitive movements relevant to AI and video understanding, and synthesize them into intelligence for internal teams

Communications & Strategic Relations Manager – APAC

DevOps Engineer

• Own production reliability end to end — from deployment through monitoring, incident response, and postmortem-driven improvement.
• Partner with the product engineering teams to ensure their services are reliable, observable, and operable by design.
• Build and maintain observability systems (metrics, logging, tracing, alerting) that give the team clear signal on system health and performance.
• Design and operate cloud infrastructure supporting AI/ML workloads.
• Drive incident response — detect, diagnose, mitigate, and prevent production issues. Build the runbooks, automation, and guardrails that reduce mean time to recovery.
• Identify and eliminate toil through automation, self-healing systems, and better tooling.

Staff Site Reliability Engineer

NLP Engineer

• You will be a vital member of our ML Data Team.
• Manage resource allocation and timelines, adjusting direction flexibly based on real-time information across all data streams in your product vertical.
• Enhance dataset and process quality through seamless collaboration with vendors and outsourcing partners.
• Establish labeling guidelines, monitor data quality, and improve tools and infrastructure to build a sustainable data operations framework.
• Partner with Engineering and AI Model teams to align on top priority data needs, design tools such as analytical reports and dashboards, and clearly communicate project progress.

Computational Linguist, AI Evaluation

Program Manager

• Design and build robust model evaluation frameworks, automating repetitive processes and maintaining a balanced approach to efficiency and depth in obtaining evaluation metrics and feedback.
• Manage resource allocation and timelines, adjusting direction flexibly based on real-time information across all data streams in your product vertical.
• Enhance dataset and process quality through seamless collaboration with vendors and outsourcing partners.
• Establish labeling guidelines, monitor data quality, and improve tools and infrastructure to build a sustainable data operations framework.
• Partner with Engineering and AI Model teams to align on top priority data needs, design tools such as analytical reports and dashboards, and clearly communicate project progress.

AI Evaluation Program Manager

• Build, improve, and operate production ML systems for Pegasus, with a focus on reliability, performance, and maintainability.
• Work across core parts of the ML stack, including deployment, inference, evaluation, monitoring, and supporting infrastructure.
• Develop systems for serving Video Language Models (VLMs) and handling multimodal data and metadata at production quality.
• Make strong technical decisions within your area and drive execution with a high degree of ownership.
• Explore and adopt AI-assisted development tools such as Claude, Gemini, and GPT to improve productivity across coding, experimentation, debugging, and documentation.

• Drive technical direction for training infrastructure and training operations within Pegasus while remaining deeply hands-on in critical system design and implementation.
• Own the design and evolution of scalable end-to-end training pipelines, with a focus on reliability, reproducibility, efficiency, and fast iteration in large-scale distributed environments.
• Lead technical decision-making across data curation workflows, training systems, evaluation pipelines, and ML infrastructure for multimodal model development.
• Improve and automate the end-to-end training lifecycle so research ideas can be translated into robust systems and integrated into production model development quickly and reliably.
• Mentor engineers and raise the team’s execution bar through strong technical judgment, design reviews, and hands-on collaboration.
• Explore and adopt AI-assisted development tools such as Claude, Gemini, and GPT to improve productivity across coding, experimentation, debugging, and documentation.

• Drive technical direction for ML engineering within Pegasus while remaining deeply hands-on in critical system design and implementation.
• Own the design and evolution of critical production ML systems for Pegasus, with a focus on scalability, reliability, performance, and fast iteration.
• Lead technical decision-making across model deployment, inference architecture, metadata systems, and ML infrastructure for Video Language Models (VLMs).
• Improve and automate the end-to-end ML lifecycle so research advances can translate into product improvements quickly and reliably.
• Mentor engineers and raise the team’s execution bar through strong technical judgment, design reviews, and hands-on collaboration.
• Explore and adopt AI-assisted development tools such as Claude, Gemini, and GPT to improve productivity across coding, experimentation, debugging, and documentation.

Staff Machine Learning Engineer

• Lead complex ML systems work across Pegasus from design through production, especially in areas with greater technical ambiguity or system complexity.
• Make strong design and architectural decisions across deployment, inference, evaluation, monitoring, and ML infrastructure within your domain.
• Improve critical parts of the ML lifecycle so research advances can be integrated into production quickly and reliably.
• Drive improvements to model serving, inference architecture, and ML workflows for Video Language Models (VLMs) in production.
• Support other engineers through technical guidance, design reviews, and strong engineering judgment.
• Explore and adopt AI-assisted development tools such as Claude, Gemini, and GPT to improve productivity across coding, experimentation, debugging, and documentation.

Lead Product Manager, Embedding, Search

Director of Partner Engineering

Solutions Architect

Staff Machine Learning Engineer – TrainingOps

Communications & Strategic Relations Manager – APAC

Staff Site Reliability Engineer

Computational Linguist, AI Evaluation

AI Evaluation Program Manager

Machine Learning Engineer

Staff Machine Learning Engineer – TrainingOps

Staff Machine Learning Engineer

Senior Machine Learning Engineer