GPU Performance Engineer

About the Company

Genmo is a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. We are shaping the future of AI and pushing the boundaries of what's possible in video generation.

Responsibilities

• Profile and optimize GPU workloads using Nsight Systems, nvprof, and custom instrumentation
• Write high-performance CUDA and Triton kernels for critical model operations
• Optimize cold start latency from seconds to milliseconds for serving infrastructure
• Tune memory access patterns, kernel fusion, and GPU utilization
• Collaborate with ML engineers to optimize model implementations
• Debug performance issues across the full stack from application to hardware
• Implement custom memory pooling and allocation strategies
• Share optimization techniques and build performance culture across teams

Requirements

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
• 5+ years systems programming experience
• 3+ years focused on GPU optimization
• Expert proficiency with GPU profiling tools (Nsight Systems, nvprof)
• Strong CUDA programming skills with production kernel development
• Deep understanding of GPU architecture (memory hierarchy, SMs, warps)
• Track record of achieving significant performance improvements (5-10x)
• Experience with Python and C++ in production environments

Preferred Qualifications

• Experience with Triton kernel development
• Knowledge of CUTLASS or similar high-performance libraries
• Background in ML-specific optimizations (attention, transformers)
• RDMA/InfiniBand optimization experience
• Contributions to GPU libraries or frameworks
• Low-level debugging skills (PTX/SASS reading)