Luma AI
Research Scientist / Engineer – Training Infrastructure
$195K–$395K
Redwood City, CA +7 · Hybrid · Full-time · Posted Oct 8, 2026
- Location
- Redwood City, CA
Remote, US
Remote, EU
New York, NY
Remote, INT
Seattle, WA
London, UK
Remote, UK
About the job
Builds and optimizes distributed training infrastructure for large-scale multimodal models across thousands of GPUs.
What you'll do
- Design and optimize distributed training systems for models across thousands of GPUs.
- Research and implement advanced parallelization, including FSDP, Tensor Parallel, Pipeline Parallel, and Expert Parallel.
- Build monitoring, visualization, and debugging tools; improve training stability, convergence, and resource utilization.
What they ask for
- Extensive distributed PyTorch training and parallelism experience in foundation-model training.
- Deep understanding of GPU clusters, networking, and storage systems.
- Familiarity with NCCL and MPI communication libraries and distributed-system optimization.
Nice to have
- Strong Linux systems administration and scripting.
- Experience managing runs across 100+ GPUs; containerization, orchestration, and cloud infrastructure experience.
Pay
$195K – $395K (base salary)
Tools
PyTorch, CUDA, FSDP, Tensor Parallel, Pipeline Parallel, Expert Parallel, NCCL, MPI
AI focus
Supports training large-scale multimodal foundation models.
Model-written summary · the original posting is authoritative