Luma | Dream Lab
Research Scientist / Engineer – Training Infrastructure
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About Luma
Luma’s mission is to build [multimodal AI] to [expand human imagination and capabilities]. We believe 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
- Eventually [interact with our world to effect change]
About The Role
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
- Distributed systems
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You will work alongside the rest of the [research team] to build & train cutting-edge foundation models on thousands of GPUs that are designed to scale from the ground up.
Responsibilities
- Design, implement, and optimize efficient [distributed training systems] for models with thousands of GPUs
- Research and implement advanced parallelization techniques:
- FSDP (Fully Sharded Data Parallel)
- 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]
Experience
Core Requirements
- Extensive experience with:
- Distributed PyTorch training
- Parallelisms in foundation model training
- Deep understanding of:
- GPU clusters
- Networking
- Storage systems
- Familiarity with:
- Communication libraries (NCCL, MPI)
- Distributed system optimization
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Preferred
- Strong [Linux systems administration] and scripting capabilities
- Experience managing training runs across [>100 GPUs]
- Experience with:
- Containerization
- Orchestration
- Cloud infrastructure
Compensation
The [base pay range] for this role is [$187,500 – $395,000 per year].
About Luma
[Luma’s mission] is to build [unified general intelligence] that can:
- Generate
- Understand
- Operate in the physical world
We believe [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]
- Systems that can [see and understand]
- Show and explain
- Eventually [interact with our world to effect change]
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