ML Research Engineer, Video Cognition System

Who we are

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!

About the Team

The Video Cognition System team is building the world's first video cognition system that transforms raw video archives containing millions of hours of footage into a queryable, structured Video Memory & Cortex accessible to vertical LLM agents.

We're tackling foundational questions about what constitutes machine cognition: perception, memory, reasoning, and attention. We design what and how memory should be structured for machines that go beyond the context window, and build the cortex that can reason across an entire archive of videos.

Our work spans corpus-level reasoning, knowledge extraction, indexing architectures, tool-based operations, multi-video understanding, and agentic workflows. This requires a close partnership between research and engineering, and we care deeply about building systems that are both scientifically rigorous and practically impactful.

Our research team has access to the most advanced chips in the world, including NVIDIA B300s, to push the boundaries of video cognition and understanding systems—accelerating our research-to-production cycle as fast as possible.

About the Role

This position spans two tracks—Research Scientist and Research Engineer—determined by your strengths and interests. These roles exist on a spectrum rather than as discrete categories; both contribute to research and implementation.

As a Research Scientist, you will explore fundamental questions in video reasoning, retrieval-guided QA, and multimodal understanding, driving research from hypothesis formulation to experiment design and analysis. You’ll investigate how video agents can interpret long-form content, connect evidence across modalities, and deliver reliable, structured outputs that reflect real user needs.

As a Research Engineer, you will focus on translating research ideas into robust, scalable systems. You’ll build and optimize pipelines that support indexing, retrieval, and agentic workflows, and develop the infrastructure that accelerates experimentation and ensures our models perform reliably in production. Your work will bridge the gap between exploratory research and the systems that power real-world applications.

Both tracks contribute to advancing our video agent capabilities, and both require a balance of curiosity, technical depth, and collaborative problem solving.

You might be a great fit if you have

We’re looking for candidates with research or engineering experience in areas related to video understanding, multimodal retrieval, temporal reasoning, or agent-driven workflows that combine models, tools, and structured search. You should be able to define meaningful research questions, design experiments, and drive projects from ideation to execution while grounding your work in real user scenarios and practical constraints.

Strong proficiency in Python and PyTorch is essential, along with the ability to clearly communicate technical concepts and collaborate across science, engineering, and product teams. Experience in building AI/ML agents and bringing them into production environments is highly preferred. This includes designing agent architectures, integrating them with retrieval or reasoning systems, and deploying them as reliable, user-facing components.

We evaluate based on relevant technical skills and research experience rather than degrees alone, though this is typically supported by an MS/PhD or equivalent practical experience in a relevant field.

What makes this role unique

The team sits at the intersection of models, retrieval, reasoning, and user workflows. The systems you build will rapidly make their way into real products used by customers worldwide. We operate with a tight research-to-production loop, ensuring that innovations have immediate, meaningful impact.

Others

• Work Location: Seoul Itaewon office + Pangyo satellite office

• Additional Info: 전문연구요원 편입/전직 가능합니다.

Even if you don't check every box, we encourage you to apply. If you're a zero-to-one achiever, a ferocious learner, and a kind team player who motivates others, you'll find a home at TwelveLabs.

Hiring Process

Application Review → Recruiter Interview (비대면/30분) → Hiring Manager Interview (비대면/30분) → Technical Interview Round 1 (대면/60분) → Technical Interview Round 2 (비대면/90분) → Final Round Interview (비대면/45분) → Reference Check → Offer

Benefits and Perks

• Growth & Tools

  • 글로벌 B2B 고객과 함께 성장하는 Global Team

  • 자율성과 협업을 모두 갖춘 하이브리드 근무

  • 최신 맥북 및 70만 원 상당 재택근무 장비 지원, 3년 주기로 최신 장비 교체

  • Tokens never sleep - Tech 직군 LLM 토큰 무제한 지원

  • 강의, 컨퍼런스, 멤버십 등에 사용 가능한 연 140만원 상당 자기개발비 지원

  • 영어 교육 프로그램 및 글로벌 버디 프로그램 운영

  • 야간 및 주말 출퇴근 택시비 지원

• Meal & Snack

  • 식비·교통비 등 자유롭게 사용할 수 있는 연 720만원 상당 법인카드 제공

  • 사무실 내 스낵바 운영 (간식, 커피, 제철 과일 등)

  • 사무실 근무 시, 오후 7시 이후 저녁 식대 제공

• Wellness & Family

  • 연 1회 본인 및 가족 1인의 건강검진 제공

  • 단체보험 가입 (상해보험/치아보험/가족 상해보험 중 택 1)

  • 독감 예방접종비 지원

  • 연말 2주간 유급 Holiday Break 운영