Machine Learning Engineer developing and operating ML systems for video analysis with a focus on reliability and performance. Join TwelveLabs in pioneering multimodal AI from Seoul.
About the role
- Staff Machine Learning Engineer responsible for leading ML engineering in video AI product development. Mentoring team members and designing scalable production systems for advanced video language models.
Responsibilities
- Drive technical direction for ML engineering within Pegasus while remaining deeply hands-on in critical system design and implementation.
- Own the design and evolution of critical production ML systems for Pegasus, with a focus on scalability, reliability, performance, and fast iteration.
- Lead technical decision-making across model deployment, inference architecture, metadata systems, and ML infrastructure for Video Language Models (VLMs).
- Improve and automate the end-to-end ML lifecycle so research advances can translate into product improvements quickly and reliably.
- Mentor engineers and raise the team’s execution bar through strong technical judgment, design reviews, and hands-on collaboration.
- Explore and adopt AI-assisted development tools such as Claude, Gemini, and GPT to improve productivity across coding, experimentation, debugging, and documentation.
Requirements
- Significant experience building and productionizing ML systems as a hands-on individual contributor.
- Experience driving technical direction across ML projects and making architectural decisions in complex production environments.
- Strong foundations in machine learning and deep experience with multimodal systems such as vision, language, or video-based models.
- Experience building and evolving distributed ML or data workflows, ideally in Kubernetes-based environments.
- Strong technical judgment across system design, performance, reliability, and long-term maintainability.
- A track record of mentoring engineers and creating technical leverage beyond your own individual contributions.
- Preferred qualifications include experience serving or optimizing LLM/VLM systems in production, including inference optimization, throughput and latency tuning, batching, caching, or quantization.
- Experience designing and operating mission-critical AI/ML applications from 0 to 1 and scaling them in production.
- Experience with large-scale training or serving infrastructure for ML systems, including high-performance GPU environments.
- Master’s or PhD in Machine Learning, Computer Science, or a related technical field.
Benefits
- 글로벌 B2B 고객과 함께 성장하는 Global Team
- 자율성과 협업을 모두 갖춘 하이브리드 근무
- 전 직원에게 맥북 및 70만 원 상당 재택근무 장비 지원, 3년 주기로 최신 장비 교체
- 식사·교통비 등 자유롭게 사용할 수 있는 월 60만 원 한도 법인카드 제공
- 사무실 내 스낵바(간식, 커피, 신선식품 제공)
- 연말 2주간 겨울방학 운영
- 연 1회 건강검진 지원
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Staff Machine Learning Engineer overseeing training ops for multimodal AI at TwelveLabs. Pioneering video understanding technology in a global hybrid team.
Machine Learning Engineer developing and optimizing AI systems at Strava. Work includes building innovative models that enhance fitness experiences for millions of users.
Machine Learning Engineer developing AI systems for Strava's fitness platform. Working on personalized recommendations and optimizing user experiences for millions worldwide.
Machine Learning Engineer at DentalMonitoring developing and improving ML models for orthodontic treatment solutions. Engage in deep learning and computer vision tasks within a hybrid work environment.
AI/ML Engineer developing advanced solutions for federal client at Niyam IT. Focusing on AI/ML models and operational efficiency improvement in federal environments.
Senior Machine Learning Engineer at Capital Group, designing Generative AI systems to enhance investment processes. Collaborating with professionals to translate ideas into reliable, production - grade systems
Senior AI/ML Engineer designing and deploying AI/ML solutions for validation challenges at Micron. Working on machine learning models and optimization solutions to enhance product quality and validation efficiency.
Machine Learning Engineer focusing on MLOps and software engineering at flaschenpost, ensuring robust planning and operational success through ML products.
AI ML Engineer at global networking leader, shaping ML strategy and building high - performance systems. Innovating with AI technology to enhance network management and develop flagship products.