Staff Machine Learning Engineer overseeing training ops for multimodal AI at TwelveLabs. Pioneering video understanding technology in a global hybrid team.
Responsibilities
Drive technical direction for training infrastructure and training operations within Pegasus while remaining deeply hands-on in critical system design and implementation.
Own the design and evolution of scalable end-to-end training pipelines, with a focus on reliability, reproducibility, efficiency, and fast iteration in large-scale distributed environments.
Lead technical decision-making across data curation workflows, training systems, evaluation pipelines, and ML infrastructure for multimodal model development.
Improve and automate the end-to-end training lifecycle so research ideas can be translated into robust systems and integrated into production model development 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 large-scale ML systems as a hands-on individual contributor.
Experience driving technical direction across complex ML infrastructure or training systems projects and making architectural decisions in demanding engineering environments.
Strong experience with large-scale distributed training systems, training infrastructure, or large-scale data processing pipelines.
Strong foundations in machine learning and experience with multimodal systems such as vision, language, or video-based models.
Strong technical judgment across system design, performance, reliability, reproducibility, and long-term maintainability.
A track record of mentoring engineers and creating technical leverage beyond your own individual contributions.
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