# Machine Learning Systems Engineer > Raydar · Menlo Park, United States · Full-time · Posted 2026-10-15 **Salary:** USD 180,000–230,000 **Workplace:** on_site ## Description About the company Our client is a fast-growing technology company. The role Raydar is recruiting for this role on behalf of our client. Own speed and efficiency for machine learning training and serving systems, working from low-level GPU code up to multi-machine deployments. You will profile, tune and harden these systems alongside a small, senior technical group. What you'll do \- Improve GPU and system performance for model training and serving. \- Find and resolve slowdowns across the hardware, memory, software and cluster layers. \- Write low-level GPU optimizations using CUDA and Triton. \- Design and improve distributed training and serving engines. \- Own communication performance between GPUs and machines, including high-speed networking and disaggregated serving. \- Build benchmarking and regression tooling so performance improvements hold up in production. \- Co-design kernels, runtimes and models with the underlying hardware in mind. ## Requirements What we're looking for \- Hands-on experience writing custom GPU kernels for NVIDIA hardware. \- Has built core capabilities inside a widely used model training or serving framework, rather than only deploying or integrating it. \- Degree in computer science or a related quantitative field; recent graduates should come from a top program. \- A year or more of current, professional experience in machine learning infrastructure or GPU tuning. \- Track record of speeding up model execution at the hardware, runtime and multi-machine levels. \- Strong grounding in machine learning and computer science fundamentals. Bonus points \- Background tuning generative models that work with visual or other non-text data. ## Benefits Compensation and benefits \- Base salary: USD 180,000 to 230,000 per year \- Equity Location and work model \- California, United States \- On-site, 5 days a week in the office \- Full-time ## Apply [Apply at Raydar](https://apply.workable.com/raydar/j/B5490C5A2B/apply) --- Powered by [Workable](https://www.workable.com)