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Luma AI

AI Data Manager

Reposted 14 Days Ago
Be an Early Applicant
Remote or Hybrid
Hiring Remotely in London, Greater London, England, GBR
Mid level
Remote or Hybrid
Hiring Remotely in London, Greater London, England, GBR
Mid level
The AI Data Manager will design data annotation strategies, manage data pipelines, and collaborate with researchers to enhance AI models.
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AI Data Manager

About Luma AI
Luma's mission is to build multimodal AI to expand human imagination and capabilities. We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable, and useful systems, the next step in function change will come from vision. So we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.

The Role / Where You Come In
This is not a standard data management role; it’s a rare opportunity to be at the absolute frontier, shaping the data that trains our foundational models. You'll be the architect behind the datasets that power our generative video technology, working in close concert with our world-class research team to fuel the breakthrough models that millions of creators use. Think of yourself as the bridge between raw information and AI brilliance—you'll build the curation strategies, annotation workflows, and quality systems that help our models see and understand the world better.

What You'll Do
This is not a maintenance role; it's a zero-to-one opportunity to build the data foundation for our AI. You will:
  • Translate researcher needs into actionable data annotation and curation strategies for our SOTA vision, 3D, and audio models.
  • Own and manage end-to-end data pipelines and annotation workflows, collaborating with external partners and labeling teams to ensure the highest quality data.
  • Provide horizontal management across multiple data pipelines, ensuring consistency and quality as we expand into new modalities.
  • Develop innovative data curation strategies, working with a diverse mix of human-annotated, raw, and synthetic data to solve complex model challenges.
  • Partner directly with researchers to diagnose model performance issues and propose data-driven solutions to improve results.
  • Define the standards for data quality and annotation excellence, establishing the foundation for how Luma scales its data operations.

What We're Looking For
  • You have 2+ years of hands-on experience in AI data operations, human data annotation, or a similar data-centric role within a top-tier AI company.
  • You have direct experience translating complex researcher needs into effective data curation and annotation workflows.
  • You are highly adaptable and thrive on cross-functional collaboration, with a proven ability to work across a comprehensive data pipeline, not just within a single vertical like human annotation.
  • You have experience working with vision or multimodal data pipelines.
  • You are a hands-on individual contributor who is driven by the work, not by people management.

What Sets You Apart / Bonus Points
  • Experience working at a company known for its SOTA vision models.
  • Experience at a top-tier data labeling provider.
  • You are comfortable working with a variety of data types beyond human annotations, including raw and synthetic data.
  • You have experience managing vendor relationships for data labeling and annotation.
  • You thrive in a fast-paced startup environment and have a history of taking high ownership of your work.

Compensation
The base pay range for this role is $140,000 – $260,000 per year.
About Luma

Luma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.

We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.

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