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
Skills Required
- Hands-on experience writing custom GPU kernels for NVIDIA hardware
- Experience building core capabilities inside a widely used model training or serving framework
- Degree in computer science or a related quantitative field
- At least one year of current professional experience in machine learning infrastructure or GPU tuning
- Track record of improving model execution speed at hardware, runtime, and multi-machine levels
- Strong grounding in machine learning and computer science fundamentals
- Background tuning generative models for visual or other non-text data
What We Do
Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.
