Senior CUDA Kernel & Performance Engineer

General Motors; Washington; Hybrid; USD 170,000 - 258,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Hybrid work option

Competitive compensation package

Job summary

General Motorsis seeking a skilled GPU kernel developer to design, implement, and optimize CUDA-based kernels for on-vehicle inference workloads. You will profile performance, build tooling, and collaborate with AI Solutions, Compilers, and Architecture to map requirements into kernel roadmaps.

You should have 2+ years of relevant experience, strong C++ skills, and a solid background in high-performance computing. This hybrid role offers opportunities to impact autonomous driving tech.

Qualifications

• Minimum 2+ years of relevant industry experience or equivalent experience.
• BS, MS or PhD in CS, or related technical field.
• Excellent GPU programming skills in CUDA, with a thorough understanding of parallel programming patterns and GPU architecture.
• Hands-on experience benchmarking, profiling, debugging and optimizing accelerator libraries and kernels to extract optimal performance using the NSight suite of tools or similar.
• Strong background in software architecture, library design, and design patterns.
• Strong C++ programming skills with the ability to feel comfortable in large codebases.
• Solid background in system performance, high performance computing and/or architecture-aware optimizations.
• Strong communication skills and the ability to work collaboratively within a team.
• Excellent analytical and problem-solving skills

Responsibilities

• Design, implement, benchmark, and iterate on CUDA-based kernels and custom operators to squeeze every last drop of performance out of on-vehicle inference workloads.
• Build and improve tooling and infrastructure that make it easier to profile, debug, and validate CUDA kernels and accelerator-backend code across the AV stack.
• Partner with AI Solutions, Compilers, and Architecture to translate model and system requirements into concrete kernel roadmaps, priorities, and project plans.
• Collaborate with cross-functional teams (compiler, performance tooling, runtime, deployment solutions) to deliver reusable, reliable, high-performance libraries into production.
• Maintain high technology standards, methodologies, processes, and guidelines for GPU kernel development and performance engineering through code review.
• Manage relationships with internal customers to ensure our kernels and libraries meet real-world needs

Skills

CUDA

C++

GPU kernel programming

Performance profiling

Kernel development

Parallel programming

Software optimization

Education

BS/MS/PhD in CS or related field

Tools

CUTLASS

CuTe

Nsight tools

Job description

General Motorsis seeking a skilled GPU kernel developer to design, implement, and optimize CUDA-based kernels for on-vehicle inference workloads. You will profile performance, build tooling, and collaborate with AI Solutions, Compilers, and Architecture to map requirements into kernel roadmaps.

You should have 2+ years of relevant experience, strong C++ skills, and a solid background in high-performance computing. This hybrid role offers opportunities to impact autonomous driving tech.