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Full-Time

Software Engineer

Data

Confirmed live in the last 24 hours

Twelve Labs

Twelve Labs

51-200 employees

AI system for video content understanding

Hardware
AI & Machine Learning
Entertainment

Senior, Expert

San Francisco, CA, USA

Category
Backend Engineering
Software Engineering
Required Skills
Python
Go
Requirements
  • 7+ years of industry experience (or 4+ with a PhD in a related technical domain)
  • A PhD, or a Master's degree, in machine learning or a closely related discipline
  • Led teams of 3+ engineers as a technical lead
  • Experience building model-bootstrapped language or vision-language datasets (RLAIF, etc.)
  • Managed data acquisition for large generative or contrastive models
  • Experience with FFmpeg or other high performance image/video processing libraries (bonus points for past work with such processing on GPUs/accelerators)
  • Deep experience as a backend and/or data engineer & an interest in ML/AI systems
  • Strong Python expertise and considerable prior work history with at least one statically typed language (we use Golang)
  • Strong communication skills in written and spoken English
Responsibilities
  • Acquire, filter, label (leveraging techniques like RLAIF), and sanitize large-scale vision-language datasets for LLM/VLM pretraining
  • Scale our data systems to enable our evolution from double-digit to triple-digit billion parameter models (and beyond!)
  • Mentor junior engineers/researchers, and hold a high bar around code quality / engineering best practices
  • Establish strong relationships with 3rd party data vendors and human-in-the-loop data labeling services
  • Build the highest impact, not the flashiest, libraries and services
  • Lead by example in interviewing, hiring, and onboarding passionate and empathetic engineers
  • Work across teams to understand and manage project priorities and product deliverables, evaluate trade-offs, and drive technical initiatives from ideation to execution to shipment

Twelve Labs focuses on artificial intelligence and video understanding by developing a system that analyzes videos to extract key features like actions, objects, and speech. This information is transformed into vector representations, enabling fast semantic search within large video datasets. The company differentiates itself by providing a platform that is faster and more effective than many existing models, allowing developers and product managers to easily integrate its technology through an API. The goal is to make video content easily searchable and accessible for various industries.

Company Stage

Seed

Total Funding

$37.2M

Headquarters

San Francisco, California

Founded

2021

Growth & Insights
Headcount

6 month growth

36%

1 year growth

116%

2 year growth

346%
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Simplify's Take

What believers are saying

  • The recent $50 million Series A funding, co-led by NEA and NVIDIA's NVentures, provides substantial financial backing for future growth and innovation.
  • Partnerships with companies like CineSys and EMAM highlight Twelve Labs' expanding influence and potential for transformative industry collaborations.
  • Recognition as a 2023 Technology Pioneer by the World Economic Forum underscores the company's leadership and innovative capabilities in the AI sector.

What critics are saying

  • The rapidly evolving AI and video understanding market could see increased competition, potentially challenging Twelve Labs' market position.
  • Dependence on continuous technological advancements and high R&D costs may strain financial resources if not managed effectively.

What makes Twelve Labs unique

  • Twelve Labs' AI system excels in extracting and transforming video content into vector representations, enabling fast and scalable semantic search, which is a significant edge over traditional video search technologies.
  • The company's focus on providing an end-to-end infrastructure through an easy-to-integrate API makes it highly accessible for developers and product managers.
  • Their technology's ability to outperform both open-source and commercial models in video understanding sets them apart in the competitive AI landscape.