Systems/GPU Research Engineer

About Us

Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.

We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.

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.

LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.

About the Role

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:

• 15 min - Initial screening (virtual)

• 45 min - Quick dive into Vast, work history (virtual)

• 45 min - Systems and architectures (virtual)

• 1 hour - LLM-assisted coding assessment (virtual)

• 2 hours - Meet and greet with coding assessment (on-site)

Our goal is to complete the interview process in two weeks.

Benefits

• Comprehensive health, dental, vision, and life insurance

• 401(k) with company match

• Meaningful early-stage equity

• Onsite meals, snacks, and close collaboration with founders/tech leaders

• Ambitious, fast-paced startup culture where initiative is rewarded