Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

The AI Kernels team builds high-performance GPU kernels and custom libraries that are central to our on-vehicle ML inference for ADAS and autonomous driving. We are responsible for making core AI workloads faster, more reliable, and easier to maintain and deploy on real cars, under real-world constraints. This involves designing and implementing custom operators, integrating kernels into our ML runtime stack, and debugging and tuning GPU performance across the AV software stack.

Responsibilities

Design, implement, benchmark, and iterate on CUDA-based kernels and custom operators to optimize on-vehicle inference workloads.
Build and improve tooling and infrastructure for profiling, debugging, and validating CUDA kernels and accelerator-backend code.
Partner with AI Solutions, Compilers, and Architecture to translate model and system requirements into kernel roadmaps and project plans.
Collaborate with cross-functional teams to deliver reusable, reliable, high-performance libraries into production.
Maintain high technology standards for GPU kernel development and performance engineering through code review.
Manage relationships with internal customers to ensure kernels and libraries meet real-world needs.

Requirements

Minimum 2+ years of relevant industry experience or equivalent.
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 using the NSight suite of tools or similar.
Strong background in software architecture, library design, and design patterns.
Strong C++ programming skills with ability to work in large codebases.
Solid background in system performance, high performance computing and/or architecture-aware optimizations.
Strong communication skills and ability to work collaboratively.
Excellent analytical and problem-solving skills.

Skills

CUDA
Parallel programming
GPU architecture
Benchmarking
Profiling
Debugging
Optimization
NSight
Software architecture
Library design
Design patterns
C++
System performance
High performance computing
Architecture-aware optimizations
Communication
Analytical skills
Problem-solving
Tensor core programming
CUTLASS
CuTe
ML model architectures
Transformer-based models
Low latency systems
Real-time systems
Accelerator software stack (drivers, runtimes, compilers)

Location

Hybrid

Work Type

Hybrid

Experience Level

2+ years of relevant industry experience or equivalent

Education Level

BS, MS or PhD in CS, or related technical field

Salary/Compensations

$170,100 to $258,300

Benefits

Medical
Dental
Vision
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation & holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts

About the Company

GM's vision is Zero Crashes, Zero Emissions, and Zero Congestion.
We are building advanced automated driving technologies, including Level 4-capable fully self-driving systems.
Our mission is to create safer, more sustainable, and more accessible mobility.
We are committed to being a workplace that fosters inclusion and belonging.
We believe in making a choice every day to drive meaningful change through our words, deeds, and culture.

Equal Opportunity

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
General Motors offers opportunities to all job seekers including individuals with disabilities.