Research Scientist / Engineer – Performance Optimization

What You'll Own

• 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.

First 90 Days

One way the first 90 could unfold.

• Days 1–30 — Immerse & Diagnose: Profile the current training and inference paths and find the biggest performance wins.

• Days 30–60 — Ship & Validate: Land a kernel or architecture optimization that measurably improves utilization or latency.

• Days 60–90 — Scale & Systemize: Build the monitoring and automation that keeps performance gains from regressing.

What You Bring

• 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.

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.

About Luma: 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. Luma is an equal opportunity employer.