Luma AI’s mission is to build Multimodal AGI
The Role
Seeking a Research Scientist/Engineer to design and optimize distributed training systems for large-scale multimodal AI models using thousands of GPUs.
Summary Generated by Built In
About Luma AI
About the Role
Responsibilities
Experience
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.
The Training Infrastructure team at Luma is responsible for building and maintaining the distributed systems that enable training of our large-scale multimodal models across thousands of GPUs. This team ensures our researchers can focus on innovation while having access to reliable, efficient, and scalable training infrastructure that pushes the boundaries of what's possible in AI model development. We are looking for engineers with significant experience solving hard problems in PyTorch, CUDA and distributed systems. You will work alongside the rest of the research team to build & train cutting edge foundation models on thousands of GPUs that are built to scale from the ground up.
- Design, implement, and optimize efficient distributed training systems for models with thousands of GPUs
- Research and implement advanced parallelization techniques (FSDP, Tensor Parallel, Pipeline Parallel, Expert Parallel)
- Build monitoring, visualization, and debugging tools for large-scale training runs
- Optimize training stability, convergence, and resource utilization across massive clusters
- Extensive experience with distributed PyTorch training and parallelisms in foundation model training
- Deep understanding of GPU clusters, networking, and storage systems
- Familiarity with communication libraries (NCCL, MPI) and distributed system optimization
- (Preferred) Strong Linux systems administration and scripting capabilities
- (Preferred) Experience managing training runs across >100 GPUs
- (Preferred) Experience with containerization, orchestration, and cloud infrastructure
The base pay range for this role is $187,500 – $395,000 per year.
About LumaLuma’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.
Skills Required
- Extensive experience with distributed PyTorch training and parallelisms in foundation model training
- Deep understanding of GPU clusters, networking, and storage systems
- Familiarity with communication libraries (NCCL, MPI) and distributed system optimization
- Strong Linux systems administration and scripting capabilities
- Experience managing training runs across >100 GPUs
- Experience with containerization, orchestration, and cloud infrastructure
Luma AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Luma AI and has not been reviewed or approved by Luma AI.
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Fair & Transparent Compensation — Pay is considered competitive for senior technical and some non-technical roles, with posted bands indicating strong market alignment in key locations. Publicly listed ranges provide directional clarity for certain roles and markets.
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Equity Value & Accessibility — Equity is positioned as a meaningful component of total compensation, and language in postings emphasizes ownership alongside cash pay. Signals indicate equity can be significant in senior roles where competition for talent is intense.
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Healthcare Strength — Core medical, dental, and vision coverage are referenced in multiple postings, aligning with standard expectations for venture-backed tech companies. These inclusions suggest baseline health benefits are part of the package.
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The Company
What We Do
Luma AI’s mission is to build Multimodal AGI: AI that can generate, understand, and operate in the physical world. We develop multimodal models across video, 3D, and generative media, and ship them in products like Dream Machine to help creators and teams turn ideas into compelling visuals—fast.
