Engineering Manager, Data at Twelve Labs

Seoul, South Korea

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, Video AIIndustries

Requirements

6명 이상의 데이터 혹은 엔지니어링 팀을 4년 이상 리딩한 경험
8년 이상의 소프트웨어 엔지니어링 경력과 뛰어난 기술 리더십 보유
데이터 혹은 ML 엔지니어의 채용, 온보딩, 멘토링을 통해 팀의 성장을 이끈 경험
대규모 데이터 시스템을 설계 및 운영해 본 실질적인 경험
Preferred Qualifications
5명 이상의 시니어 엔지니어를 성공적으로 채용하고 성과를 낸 경험
AI/ML 기반의 핵심 제품을 처음부터 설계하고 출시까지 리딩한 경험
ML 시스템 또는 데이터 인프라를 페타바이트(PB) 규모로 확장해 본 경험
Python 기반의 데이터 플랫폼 및 분산 처리 시스템(Spark, Kafka 등)을 실무에서 설계·운영해 본 경험

Responsibilities

팀 빌딩 및 기술 문화 구축: ML 데이터 엔지니어링 팀을 리드하며, 팀의 미션과 기술 전략을 정의하고 실행. 팀의 채용 계획 수립 및 실행을 통해 우수한 인재를 유치하고, 코드 리뷰와 기술 멘토링을 통해 높은 수준의 엔지니어링 문화를 만듦
멀티모달 ML 데이터 엔진 설계 및 운영: AI 모델 학습을 위한 페타바이트(PB) 규모의 비디오, 이미지, 오디오 데이터를 수집·정제·라벨링하는 파이프라인을 설계하고 운영. VLM/LLM 학습용 데이터셋 자동 생성 시스템 및 고정밀 전처리 엔진을 구축
멀티모달 ML 데이터 인프라 설계 및 운영: 대규모 데이터를 안정적으로 처리할 수 있는 확장 가능한 데이터 인프라를 설계하고 운영
데이터 전략 수립 및 실행: PM, 리서치, 인프라, 제품 등 다양한 조직과 긴밀히 협업하여, 회사의 비전과 일치하는 데이터 전략을 수립하고 우선순위를 조정하며 실행

Skills

Key technologies and capabilities for this role

Data PipelinesMultimodal Data ProcessingVideo ProcessingData LabelingScalable Data InfrastructureLLM Data GenerationVLM DatasetsData PreprocessingTeam LeadershipTechnical ArchitectureCode ReviewMentoring

Questions & Answers

Common questions about this position

What is the work arrangement for this position?

The position is hybrid, combining autonomy and collaboration in a hybrid work setup.

What are the key requirements for this role?

Candidates need 4+ years leading data or engineering teams of 6+ people, 8+ years of software engineering with strong technical leadership, experience growing teams through hiring/onboarding/mentoring, and hands-on experience designing/operating large-scale data systems.

What is the salary for this position?

This information is not specified in the job description.

What are some of the benefits offered?

Benefits include MacBook and 700,000 KRW home office equipment support with replacement every 3 years, monthly 600,000 KRW corporate card for meals/transport, office snack bar, 2-week year-end winter break, annual health checkup, and English education program.

What does Twelve Labs value in its company culture?

The company values honesty and reflection about self and team, perseverance and humility without fearing failure or feedback, continuous learning to elevate team capabilities, and enjoying the growth process while solving challenging problems together.

Twelve Labs

AI system for video content understanding

About Twelve Labs

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. Twelve Labs aims to make all videos searchable, enhancing the way businesses utilize video content.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$104.2MTotal Funding

EARLY_VCCompany Stage

Enterprise Software, AI & Machine Learning, EducationIndustries

51-200Employees

Risks

Increased competition from emerging AI startups in video understanding.

Rapid AI advancements require continuous innovation, straining resources.

Potential over-reliance on key investors like SK Telecom and Databricks.

Differentiation

Twelve Labs offers a comprehensive AI system for multimodal video understanding.

Their technology transforms video content into vector representations for fast semantic search.

The platform's API allows easy integration into clients' systems with minimal effort.

Upsides

Growing demand for AI-driven video analytics in education, healthcare, and security sectors.

Recent $30 million funding enhances technology development and strategic partnerships.

Collaboration with cloud providers boosts scalability and efficiency of video processing.

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