GPU Performance Engineer
San Francisco HQ • FullTime
Posted 1y ago
Job Location
San Francisco HQ
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
Genmo is a research lab developing advanced video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking a GPU Performance Engineer to optimize our model serving stack and extract maximum performance from our H100 infrastructure. This role involves identifying bottlenecks, implementing solutions for significant speedups, and pushing hardware to its theoretical limits, with a focus on microsecond optimizations.
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 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.