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Luma AI’s mission is to build Multimodal AGI
The Role
The role focuses on optimizing AI models for efficiency, involving GPU/CPU code profiling, high-performance programming, and developing performance tools.
Summary Generated by Built In
About Luma AI
About the Role
Responsibilities
Experience
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.
The Performance Optimization team at Luma is dedicated to maximizing the efficiency and performance of our AI models. Working closely with both research and engineering teams, this group ensures that our cutting-edge multimodal models can be trained efficiently and deployed at scale while maintaining the highest quality standards.
- Profile and optimize GPU/CPU/Accelerator code for maximum utilization and minimal latency
- Write high-performance PyTorch, Triton, CUDA, deferring to custom PyTorch operations if necessary
- Develop fused kernels and leverage tensor cores and modern hardware features for optimal hardware utilization on different hardware 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 model
- Expert-level proficiency in Triton/CUDA programming and GPU optimization
- Strong PyTorch skills
- Experience with PyTorch kernel development and custom operations
- Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling)
- Deep understanding of transformer architectures and attention mechanisms
- (Preferred) Experience with compilers/exporters such as torch.compile, TensorRT, ONNX, XLA
- (Preferred) Experience optimizing inference workloads for latency and throughput
- (Preferred) Experience with Triton compiler and kernel fusion techniques
- (Preferred) Knowledge of warp-level intrinsics and advanced CUDA optimization
Your applications are reviewed by real people.
CompensationThe base pay range for this role is $187,500 – $395,000 per year.
About LumaLuma’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.
Skills Required
- Expert-level proficiency in Triton/CUDA programming
- Strong PyTorch skills
- Experience with PyTorch kernel development and custom operations
- Proficiency with profiling tools (NVIDIA Nsight, torch profiler, custom tooling)
- Deep understanding of transformer architectures and attention mechanisms
- Experience with compilers/exporters such as torch.compile, TensorRT, ONNX, XLA
- Experience optimizing inference workloads for latency and throughput
- Experience with Triton compiler and kernel fusion techniques
- Knowledge of warp-level intrinsics and advanced CUDA optimization
Luma AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Luma AI and has not been reviewed or approved by Luma AI.
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Fair & Transparent Compensation — Pay is considered competitive for senior technical and some non-technical roles, with posted bands indicating strong market alignment in key locations. Publicly listed ranges provide directional clarity for certain roles and markets.
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Equity Value & Accessibility — Equity is positioned as a meaningful component of total compensation, and language in postings emphasizes ownership alongside cash pay. Signals indicate equity can be significant in senior roles where competition for talent is intense.
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Healthcare Strength — Core medical, dental, and vision coverage are referenced in multiple postings, aligning with standard expectations for venture-backed tech companies. These inclusions suggest baseline health benefits are part of the package.
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The Company
What We Do
Luma AI’s mission is to build Multimodal AGI: AI that can generate, understand, and operate in the physical world. We develop multimodal models across video, 3D, and generative media, and ship them in products like Dream Machine to help creators and teams turn ideas into compelling visuals—fast.
