Senior Staff Research Scientist/Engineer - Analysis at TwelveLabs

Seoul, , South Korea -

Full Time

Start Date

Immediate

Expiry Date

15 Mar, 26

Salary

0.0

Posted On

15 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Multimodal Understanding, Unimodal LLMs, Large-Scale Distributed Training Systems, Data-Centric Model Development, Python, PyTorch, Communication Skills, ML Systems Deployment

Industry

Software Development

Description

Who we are At TwelveLabs, we are pioneering the development of cutting-edge multimodal foundation models that have the ability to comprehend videos just like humans do. Our models have redefined the standards in video-language modeling, empowering us with more intuitive and far-reaching capabilities, and fundamentally transforming the way we interact with and analyze various forms of media. With a $110+ million in Seed and Series A funding, our company is backed by top-tier venture capital firms such as NVIDIA’s NVentures, NEA, Radical Ventures, and Index Ventures, and prominent AI visionaries and founders such as Fei-Fei Li, Silvio Savarese, Alexandr Wang and more. Headquartered in San Francisco, with an influential APAC presence in Seoul, our global footprint underscores our commitment to driving worldwide innovation. We are a global company that values the uniqueness of each person’s journey. It is the differences in our cultural, educational, and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI. About the Team The Analysis team sits at the core of TwelveLabs’ video understanding capabilities and is responsible for driving our Video Analysis product. We design multimodal video analysis systems that ingest video input to accurately answer a wide variety of user questions. We focus on shipping products with real-world value rather than doing research in isolation, and we work very closely with ML Engineers in a goal-oriented, cross-functional team. Our research covers a broad range of challenges: multimodal understanding of video content across visual and audio streams, accurate temporal segmentation and semantic information extraction for real-world use cases, extending temporal context length to multiple hours, and data curation processes that enable well-aligned evaluation and performance improvements through training data enhancements. 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 define research problems, formulate hypotheses, and run experiments that push the boundaries of what’s possible in video analysis. You’ll design data curation processes that accurately translate real-world use cases into tangible evaluation methods. You’ll improve the performance of our Video Analysis system through data-centric approaches and architecture exploration, supported by rigorous ablation studies. As a Research Engineer, you will translate research ideas into stable, reproducible systems. You’ll help scale the data curation process for both evaluation and training by building research infrastructure and collaborating with data engineers. You’ll design and optimize training pipelines for large-scale distributed environments and ensure our models perform reliably in production. In both roles, you will communicate key findings to the team and help shape our strategic direction. You’ll take end-to-end ownership of the Video Analysis product and collaborate closely with ML Engineers to ensure research results are delivered with real-world impact. You might be a great fit if you have We’re looking for candidates with research experience in areas that align with our challenges: multimodal or unimodal LLMs, large-scale distributed training systems, and data-centric model development. Your experience should be demonstrated through past projects, concrete contributions, and research outputs. You should be capable of independently driving research from ideation to execution. Strong proficiency in Python and PyTorch is essential, as is the ability to communicate effectively with colleagues from diverse backgrounds. Experience deploying ML systems in production and strong communication skills in English are significant pluses. 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 gap between research and production is remarkably short. Models and systems you build will be used by thousands of customers worldwide within months. As an early-stage and relatively small startup, we are uniquely positioned to tackle video understanding at production-grade quality and scale. As a member of the Analysis team, you will have strong ownership of the Video Analysis product, with clear visibility into the real-world impact of your research. 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/30분) → Reference Check → Offer

Responsibilities

The role involves defining research problems, formulating hypotheses, and running experiments in video analysis. Additionally, it includes translating research ideas into stable systems and collaborating with ML Engineers to ensure real-world impact.