Senior Software Engineer, AI Storage

NVIDIA•Santa Clara, CA

1d•$184,000 - $287,500

About The Position

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most inquisitive people in the world. Join us at the forefront of technological advancement.

Requirements

Good knowledge of Linux kernel internals, Filesystem, Object storage systems, Databases, Vector Databases
Good understanding of NVMe and related technologies
Development experience in Cloud, Virtualization (VMware, KVM), Container technologies.
Advanced knowledge in Computer Architecture
Solid understanding in data structures and algorithms
Bash and Python experience
Excellent communication and planning skills.
BS or MS or PhD in computer science or a related field or equivalent experience.
7+ years of strong coding experience using C, C++, Rust, Python

Nice To Haves

Development experience in storage software such as Key-Value, File systems object storage systems, Vector Databases
Internals of frameworks like PyTorch, JAX
Exceptional CUDA programming skills.
Exceptional C++ programming skills

Responsibilities

Work on first solutions in the industry that bring exceptional performance and security improvements to the infrastructure used by leading applications.
Develop new features and enable various technologies around data storage for GPU IO.
Develop advanced C++/CUDA libraries and algorithms for speed-of-light performance
Remove performance bottlenecks by coming up with optimization(s) in the IO stack, frameworks, and applications.
Work collaboratively with other specialists including the research teams and be willing to take on complex engineering tasks that progress towards the goals of the team and the company.