Software Engineer, Machine Learning

Twelve Labs Inc.

Job Overview

Location

Seoul, South Korea

Job Type

Full-time

Full Job Description

📋 Description

• As a Software Engineer, Machine Learning at Twelve Labs Inc., you will play a critical role in ensuring that the company’s cutting-edge Video AI models are reliably deployed and served in production environments, directly enabling real-world impact for global customers in sports, media, security, and beyond.
• Your work will bridge the gap between research breakthroughs and scalable, user-facing products by building robust backend systems that power video search, analysis, summarization, and insight generation at scale.
• You will design and implement serving architecture and inference-facing backend systems that ensure Twelve Labs’ core Video AI products operate stably and efficiently in customer environments, handling high-throughput, low-latency demands with fault tolerance.
• You will develop and evolve platform systems that both Product and Research teams can leverage, creating a reusable foundation for iterative model development, testing, and deployment across the ML lifecycle.
• You will define and implement end-to-end backend architectures that integrate multiple systems — from model training to serving — ensuring reliability, scalability, and usability are met throughout the operational lifecycle.
• You will build production-grade systems using Python and/or Go within Kubernetes-based environments, optimizing for efficient utilization of large-scale GPU resources (including H100, B300, L40s) and stable processing of massive video datasets.
• You will collaborate closely with Research, Product, and Infrastructure teams to align system design with model innovation and user needs, fostering a feedback loop where product usage informs model improvement and vice versa.
• You will tackle complex Video AI/ML backend challenges, rapidly learning new domains and system problems while taking ownership of ambiguous, open-ended technical challenges in a fast-moving, experimental culture.
• You will contribute to a globally distributed team spanning Seoul and San Francisco, where mutual respect, open feedback, and continuous learning are core values, and where your work helps advance Twelve Labs’ mission to set the global standard for video understanding AI.

🎯 Requirements

• Experience designing and implementing large-scale distributed systems
• Experience designing end-to-end backend architectures for complex, interconnected systems
• Experience developing or operating services in Kubernetes-based environments
• Proficiency in Python and/or Go for building production-grade backend systems
• Experience working on systems where high throughput, reliability, and fault tolerance are critical
• Strong execution skills: ability to take complex designs through to fully operational, production-ready systems
• Interest in or motivation to quickly learn and expand expertise in Video AI/ML system backend domains
• Enjoyment of learning, experimenting, and solving complex problems through structured thinking in fast-changing environments

🏖️ Benefits

• Opportunity to grow with a global team serving international B2B customers in sports, media, and security sectors
• Hybrid work model offering both autonomy and collaboration
• Provision of a MacBook and up to 700,000 KRW worth of remote work equipment, refreshed every three years
• Monthly corporate card with a 600,000 KRW limit for flexible use on meals, transportation, and other work-related expenses
• On-site snack bar offering snacks, coffee, and fresh food items
• Annual winter break of two weeks at year-end
• Annual health checkup support
• Support for English education programs

Skills & Technologies

Python

Kubernetes

Onsite

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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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