Raydar
Machine Learning Systems Engineer
$180K–$230K
Menlo Park, California · Full-time · Posted Oct 15, 2026
- Experience
- A year or more of current, professional experience in machine learning infrastructure or GPU tuning.
- Education
- Degree in computer science or a related quantitative field; recent graduates should come from a top program.
About the job
Optimize and harden machine learning training and serving systems, from GPU kernels to multi-machine deployments.
What you'll do
- Improve GPU and system performance for training and serving; identify bottlenecks across hardware, memory, software, and clusters.
- Write GPU optimizations and design distributed training and serving engines, including communication across GPUs and machines.
- Build benchmarking and regression tools and co-design kernels, runtimes, and models for the hardware.
What they ask for
- Hands-on experience writing custom GPU kernels for NVIDIA hardware.
- Built core capabilities in a widely used model training or serving framework, not only deployed or integrated one.
- Degree in computer science or a related quantitative field; recent graduates should come from a top program.
- At least one year of current, professional experience in machine learning infrastructure or GPU tuning; track record of speeding up model execution across hardware, runtime, and multi-machine levels.
Nice to have
- Experience tuning generative models that use visual or other non-text data.
Pay
USD 180,000 to 230,000 per year (base salary)
Tools
CUDA, Triton, NVIDIA
AI focus
Optimize machine learning model training and serving, including distributed systems and hardware-aware kernel, runtime, and model co-design.
Model-written summary · the original posting is authoritative