About the job
NVIDIA is building the next generation of compiler technologies to accelerate deep learning workloads. We are looking for an engineer to implement compiler verification software & related infrastructure in the AI space. You will be solving critical problems working alongside a diverse set of minds in GPU computing and systems software, doing what you enjoy.
Responsibilities
work closely with compiler developers to verify new and state of the art deep learning related features and components including implementing and executing functional and performance testing and benchmarking software solutions; author and review verification plans, and implement verification programs, scripts, and libraries; apply deep learning and other sophisticated techniques to implement compiler verification solutions; help identify potential or observed weaknesses in the current process, offer ideas for actions that can improve code coverage, and participate in quality initiatives and drive continuous improvement
Qualifications
Minimum
BS or MS in Computer Science, Computer/Electrical Engineering, Mathematics or related field (or equivalent experience); 3+ years programming experience in Machine Learning domain, preferably using Python; Experience working with Deep Learning frameworks such as Pytorch, Scikit Learn, JAX/XLA or TensorRT; Focused, learn quickly, and have strong analytical skills with attention to detail; Strong troubleshooting and debugging skills; Proven uses of creative thinking for solutions to exciting problems that matter
Preferred
Experience with Large Language Models and application of deep learning to solve software engineering problems; Hands-on compiler development or verification experience; Knowledge of related programming languages and domains such as CUDA, Docker and GPU-Accelerated Cloud