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About the Role
Optimize multimodal models for efficient training and scalable deployment, focusing on GPU, CPU, and accelerator code performance. Write kernels and operations to maximize hardware utilization.
Responsibilities
- Profile and optimize GPU/CPU/accelerator code for maximum utilization and minimal latency.
- Write high-performance PyTorch, Triton, and CUDA, dropping to custom operations when needed.
- Develop fused kernels and leverage tensor cores and modern hardware features across platforms.
- Optimize model architectures and implementations for distributed multi-node production deployment.
- Build performance monitoring and analysis tools and automation.
- Research and implement cutting-edge optimization techniques for transformer models.
Requirements
- Expert-level Triton/CUDA programming and GPU optimization.
- Strong PyTorch skills, including kernel development and custom operations.
- Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling).
- Deep understanding of transformer architectures and attention mechanisms.
Skills
- GPU optimization
- CPU optimization
- Accelerator code optimization
- PyTorch
- Triton
- CUDA
- Kernel development
- Custom operations
- Fused kernels
- Tensor cores
- Distributed multi-node deployment
- Performance monitoring
- Performance analysis
- Transformer models
- Compilers
- Exporters
- torch.compile
- TensorRT
- ONNX
- XLA
- Inference optimization
- Latency optimization
- Throughput optimization
- Triton compiler
- Kernel fusion
- Warp-level intrinsics
- Advanced CUDA optimization
Experience Level
- Expert-level
About the Company
- Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
- We believe multimodality is critical for intelligence — the next step beyond language models comes from vision.
Equal Opportunity
- Luma is an equal opportunity employer.