Twelve Labs Inc. logo

Staff Machine Learning Engineer - TrainingOps

Job Overview

Location

Seoul, South Korea

Job Type

Full-time

Category

Engineering

Date Posted

April 13, 2026

Full Job Description

đź“‹ Description

  • • As a Staff Machine Learning Engineer on the TrainingOps team at Twelve Labs Inc., you will drive technical direction for training infrastructure and operations within the Pegasus team, ensuring scalable, reliable, and efficient end-to-end training pipelines for multimodal foundation models that comprehend video like humans.
  • • Day to day, you will own the design and evolution of scalable training pipelines, lead technical decisions across data curation, training systems, evaluation, and ML infrastructure, improve and automate the training lifecycle from research to production, mentor engineers, and explore AI-assisted development tools to boost team productivity.
  • • The Pegasus team is at the core of Twelve Labs' video understanding capabilities, responsible for developing multimodal video analysis systems with high instruction-following and complex structured outputs, working in a goal-oriented, cross-functional environment with access to advanced hardware like NVIDIA B300s to accelerate research-to-production cycles.
  • • In this role, you will deepen your expertise in large-scale distributed ML systems, multimodal model training, and infrastructure leadership, while making a tangible impact on cutting-edge video AI technology backed by top-tier investors and strategic partnerships with NVIDIA and AWS.

Skills & Technologies

AWS
Senior
Onsite
Degree Required

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Twelve Labs Inc. logo
Twelve Labs Inc.
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About Twelve Labs Inc.

Twelve Labs builds multimodal video understanding AI. Its cloud platform transforms long-form video into vector embeddings that capture visual, audio, speech and contextual information, enabling semantic search, summarization, chaptering, moderation and analytics through a single API. Developers upload video, index it, then query in natural language or image to retrieve exact moments, generate highlights or detect unwanted content. Models are pretrained on large-scale web video, continually fine-tuned for accuracy and latency, and deployable on dedicated GPU clusters for enterprise security. Founded in 2021, the San Francisco company serves media, ed-tech, safety and e-commerce customers worldwide.

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