Luma AI
Research Scientist / Engineer – Performance Optimization
Redwood City, CA
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odds of building a lasting career here
Thin sponsorship signal and lottery-bound (~15% per draw). A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
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The bottom of this range ($30,000) is below the Level I prevailing wage of $100,422. An H-1B cannot be filed below the prevailing wage, so an offer at the floor of this band could not be sponsored as posted.
DOL prevailing wage, 2026-27 wage year · Computer and Information Research Scientists (15-1221) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- You'll make Luma's multimodal models fast - profiling and optimizing GPU, CPU, and accelerator code so they train efficiently and deploy at scale without sacrificing quality.
- You'll write the kernels and operations that get the most out of the hardware.
- This is deep performance work: fused kernels, tensor cores, Triton and CUDA, distributed multi-node deployment.
Requirements
- Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling).
- Expert-level Triton/CUDA programming and GPU optimization.
- Strong PyTorch skills, including kernel development and custom operations.
- Deep understanding of transformer architectures and attention mechanisms.
Nice to have
- Experience with compilers and exporters (torch.compile, TensorRT, ONNX, XLA).
- Experience optimizing inference workloads for latency and throughput.
- Triton compiler and kernel fusion techniques.
- Knowledge of warp-level intrinsics and advanced CUDA optimization.
- Luma is an equal opportunity employer.
Compensation
- $30k-$60k
Benefits
- We believe multimodality is critical for intelligence - the next step beyond language models comes from vision.
Company info
- Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
This listing is sourced directly from Luma AI's careers page and normalized into a canonical job model.