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# Systems/GPU Research Engineer

- **Company:** VAST, INC.
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Artificial Neural Networks, C++ (Programming Language), Cloud Computing, Program Optimization, Nvidia CUDA, Computer Programming, Linux, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Software Engineering, Systems Architecture, Scripting, Graphics Processing Unit (GPU), Large Language Models, Gpu Programming
- **Published:** September 16, 2026
- **Apply:** https://www.careerbuilder.com/job-details/systems-gpu-research-engineer-san-francisco-ca--1613a607-eaf7-4dc2-8553-001be63897e3

## About the Role

We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills., Algorithms, Artificial Intelligence (AI), C++ Programming Language, CUDA (Compute Unified Device Architecture), Cloud Computing, Communication Skills, GPU (Graphics Processing Unit), Kernel Programming, Leadership, Linux Operating System, Machine Tool, Network Performance/Analysis, Neural Networks, Programming Methodologies, Prototyping, Python Programming/Scripting Language, Research Skills, Resource Management, Startup, System Architecture

## Description

As a systems/GPU engineer, you will play a crucial role in developing new kernels and algorithms that can improve inference for AI models. You will help develop new high-performance tensor libraries and auto-optimization tools. Collaborating directly with our technical founder and diverse team, you will enhance the performance and efficiency of our AI systems. Your ability to research and stay on top of cutting-edge papers will be vital in staying up-to-date with the latest advancements in AI model inference and GPU programming techniques.

 * Full-Time
 * On-site at either our SF or LA offices

Tech Stack

C++/CUDA, GPGPU, Python, Linux
Ideal Experience

 * Expertise in systems engineering across the tech stack
 * Deep understanding of GPU architectures
 * Strong holistic background in neural network performance and tooling
 * Published research at top AI conferences

Key Responsibilities

 * Develop or extend parallel generic GPU libraries and kernels
 * Help design and deploy market-based resource management systems
 * Quickly investigate and summarize options for new system architectures
 * Prototype and evaluate novel state-of-the-art methods/models
 * Investigate and learn new frameworks and tools

Interview Process

After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:

 * Initial screening (virtual, 15 minutes)
 * Quick dive into Vast, systems and architectures (virtual, 30 minutes)
 * LLM-assisted coding assessment (virtual, 1 hour)
 * Meet and greet with coding assessment (on-site, 2 hours)


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