Senior CUDA Kernel & GPU Scheduling Engineer

NVIDIA; Jasper (AL); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a seasoned system software engineer to work on the CUDA Driver, a core component of our platform for accelerating general purpose computation on the GPU. You will join a team delivering features and improvements for diverse workloads including AI, scientific computing, data science, and gaming.

We value deep design and coding expertise, with responsibility to evangelize, architecture, and implement new capabilities across multiple teams and OS platforms.

Qualifications

• BS or MS in Computer Science, Electrical Engineering or related field (or equivalent experience).
• Strong C and C++ programming skills.
• Minimum of 4 years of related development experience.
• Experience driving projects across multiple teams.
• Experience working with large codebases.
• Background with OS interfaces for threads, processes, and VM.
• Understanding of system-level architecture (interconnects, memory hierarchy, interrupts, MMIO).
• Experience writing and debugging multithreaded programs.
• Good written communication and presentation skills.

Responsibilities

• Evangelize, architect, and implement new features.
• Coordinate and drive development efforts across multiple teams.
• Help define forward-looking improvements to the CUDA APIs and programming model.
• Extend CUDA programming models and functionality such as CUDA Graphs.
• Explore Graphs to improve scheduling of AI/ML workloads on GPUs.
• Write effective, maintainable, and well-tested code.
• Develop code for multiple operating systems.

Skills

C/C++ programming

Multithreading

Operating systems

System architecture

Team collaboration

Communication skills

Education

BS/MS in CS/EE

Tools

Linux kernel

Git

Job description

NVIDIA is seeking a seasoned system software engineer to work on the CUDA Driver, a core component of our platform for accelerating general purpose computation on the GPU. You will join a team delivering features and improvements for diverse workloads including AI, scientific computing, data science, and gaming.

We value deep design and coding expertise, with responsibility to evangelize, architecture, and implement new capabilities across multiple teams and OS platforms.