GPU Performance Engineer

The role

You will optimize GPU workloads and the model serving stack on H100 infrastructure. You will use profiling tools to identify bottlenecks and implement solutions to achieve speedups.

What you will do

• 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 our 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

Required qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
• 5+ years systems programming experience with 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

Nice to have

• 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)

About the company

Genmo is a research lab developing video world models to understand, simulate, and interact with the physical world. Their mission is to unlock the right brain of AGI.