Software Engineer, GPU Performance
HeyGen, Los Angeles, Palo Alto, San Francisco, Toronto, Singapore +4
What you will do
- Use NVIDIA Nsight Systems, Nsight Compute, and PyTorch Profiler to investigate GPU utilization, kernel execution, memory bandwidth, and CPU–GPU data movement.
- Identify bottlenecks across model execution, preprocessing, and inference serving, then measure the impact of each optimization.
- Improve performance through batching, scheduling, memory management, and better GPU utilization.
- Develop or integrate high-performance GPU kernels when existing implementations limit performance.
- Build benchmarks and automated checks that catch performance regressions across representative video workloads.
- Collaborate with AI researchers and infrastructure engineers to bring optimizations into production.
- Measure the effect of changes on latency, throughput, cost, and output quality.
What you need
- Experience optimizing GPU-based AI workloads or high-performance computing systems.