
Empowering the world to visualize ideas through pioneering research and design. Try Dream Machine for free → lumalabs.ai/dream-machine

Empowering the world to visualize ideas through pioneering research and design. Try Dream Machine for free → lumalabs.ai/dream-machine
Headquarters / domain: lumalabs.ai (Palo Alto)
Flagship product: Dream Machine — web and iOS image & video generation platform
Core models: Ray3 family (Ray3, Ray3 Modify, Ray3.14) for production-quality video
Recent funding: Announced $900M Series C led by HUMAIN
Employees (approx.): 240
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Generative multimedia (image and video) creation and multimodal AI models.
Software Development
43000000
Announced $43M Series B to expand generative 3D and multimodal AI work
900000000
Announced $900M Series C with participation from AMD Ventures, Andreessen Horowitz, Amplify Partners and others; included partnership on large compute buildout
“HUMAIN-led strategic investment and participation from institutional VCs including Andreessen Horowitz, AMD Ventures, Amplify Partners, Matrix (per company reporting and coverage)”
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 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.
About The Role As a Data Infrastructure Engineer at Luma, you will play a critical role in building and scaling the data infrastructure that supports our cutting-edge multimodal AI systems. Your work will focus on developing high-throughput, large-scale data processing pipelines tailored for machine learning research and internal ML platform needs. You will collaborate closely with ML researchers and product teams to create reliable, efficient, and easy-to-use data infrastructure that empowers innovation and accelerates development. This role requires a strong foundation in distributed systems and data engineering, with an emphasis on supporting complex machine learning workflows rather than traditional product data infrastructure.
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