채용
WHO WE ARE:
At Twelve Labs, 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 remarkable $107 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 ROLE:
You will be a vital member of our ML Data Team – which leads the full spectrum of video-language data collection, labeling, and quality management. This role comes with high ownership and includes responsibilities such as defining dataset needs and requirements in consultation with our research and product teams; designing and building data pipelines; and coordinating with our vendor partners that execute at scale. You will also be responsible for automating as much of the repetitive partnership and annotation-quality-evaluation work as possible. A desire to work cross functionally and to build relationships is critical for success in this position.
YOU WILL:
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Project Management & Operations: Design and execute video-language data collection and labeling projects. Automate repetitive processes and maintain a balanced approach to efficiency and quality.
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External Partner Collaboration: Enhance project quality through seamless collaboration with vendors and outsourcing partners.
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Data Quality & Tooling Advancement: Establish labeling guidelines, monitor data quality, and improve tools and infrastructure to build a sustainable data operations framework.
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Portfolio Monitoring: Manage resource allocation and timelines, adjusting direction flexibly based on real-time information across all data streams in your product vertical.
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Internal Collaboration: 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.
YOU MAY BE A GOOD FIT IF YOU HAVE:
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5+ years of experience working in an AI focused data operations organization.
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A proven track record designing and executing large scale data projects, including gathering, labeling, and post-processing data.
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The ability to analyze messy and complex data, identify overarching patterns, and distill your findings into crisp annotation guidelines or other accessible documentation.
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Proficiency with Python, LLMs, or other popular industry tools for automation.
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Excellent communication and project management skills, and the ability to support several projects simultaneously.
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A foundational understanding of and interest in LLMs/VLMs and multimodal AI.
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Conviction that data is the key ingredient for the performance of AI models.
YOU’LL STAND OUT IF YOU HAVE:
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Experience working with third-party SDKs.
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Experience in data collection and labeling for multimodal language models.
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Experience working with research scientists and engineers.
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Experience collaborating with or managing internal annotators.
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Experience planning and operating new data tools and labeling systems.
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Expertise or interest in video-centric domains, such as sports, advertising, and content creation.
TECH STACK:
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Development & Analysis: Python (primarily pandas, Jupyter, etc.)
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Data Management & Visualization: Amazon S3, Oracle Cloud, Various data visualization tools (framework-agnostic)
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Project Management Tools: Linear, Notion
Even if there are a few checkboxes that aren’t ticked through your prior experience, we still encourage you to apply! If you are a 0-1 achiever, a ferocious learner, and a kind and fun team player who motivates others, you will find a home at Twelve Labs.
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.
BENEFITS AND PERKS:
🤝 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.
✈️ Flexible PTO and parental leave policy. Office closed the week of Christmas and New Years.
🛂 VISA support (such as H1B and OPT transfer for US employees).
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Twelve Labs 소개

Twelve Labs
Series ATwelve Labs is an AI company that develops video understanding technology using multimodal foundation models. The company provides APIs and tools for developers to build applications that can search, analyze, and generate insights from video content.
51-200
직원 수
San Francisco
본사 위치
리뷰
3.8
10개 리뷰
워라밸
4.2
보상
2.5
문화
4.0
커리어
2.8
경영진
3.2
65%
친구에게 추천
장점
Good work-life balance
Supportive team and environment
Friendly coworkers and team spirit
단점
Poor compensation/pay not competitive
Limited career advancement opportunities
Poor management and lack of direction
연봉 정보
5개 데이터
Senior/L5
Intern
Senior/L5 · Machine Learning Engineer
1개 리포트
$318,500
총 연봉
기본급
$245,000
주식
-
보너스
-
$318,500
$318,500
뉴스 & 버즈
Twelve Labs announced on the 1st that it has built an AI archive that allows users to quickly search.. - 매일경제
매일경제
News
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2w ago
Tried a bunch of “popular” AI tools for organizing recordings… some hot takes
I’ve been cleaning up a few months’ worth of recordings and video clips lately (meetings, random notes, saved content, etc.), so I figured I’d finally try some of the AI tools everyone keeps recommending. Still wanna pick one tool to be my go-to tbh. Just wanna say upfront, this is purely my personal experience. Not saying any of these are bad, just what worked / didn’t work for me.(no affiliate links, just sharing my feeling) - Otter.AI Probably the most well-known one. Transcription is solid
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3w ago
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3
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5
How do you actually go back through meeting recordings without it taking forever?
Been in grad school long enough that lab meetings have become their own kind of stress. My PI throws out ideas mid-sentence, keeps going, and I'm nodding, then I'm back at my desk and realize I've retained maybe half of it. Started recording everything a while back. (of course, with everyone’s consent before recording) It helped, but reviewing became its own problem. I'd scrub through an hour of audio trying to find one 15-second comment. Been trying a few different AI tools for this over the
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3w ago
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4
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4
Twelve Labs introduces video AI search on Gettyimagebank - 디지털투데이
디지털투데이
News
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4w ago