Research Scientist / Engineer – Training Infrastructure
Lumalabs Ai
Apply to this job SF Bay Area, CA Remote, International remote Until 8/21/2026 First posted May 25, 2026 Last posted May 25, 2026
Job description
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
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.
Responsibilities
- 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
Experience
- 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
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.
About this role
Summary
Build scalable distributed training systems for large multimodal AI models using GPUs, PyTorch, CUDA.
Job title
Research Scientist / Engineer – Training Infrastructure
Experience level
extensive experience
Industry
technology
Location requirements
SF Bay Area and remote international work allowed.
Salary
Not specified
Management role
No
Skills & keywords
Required skills
PyTorchCUDAdistributed systemsGPU clusters
Preferred skills
Linux administrationscriptingcontainerizationcloud infrastructure
Specializations
distributed systemsGPU clustersPyTorchCUDAparallelization
Locations
Structured locations inferred from the posting.
San Francisco, CA, USA
Hybrid City
Dubai International City - Dubai - United Arab Emirates
Remote City
London, UK
On-site City
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