Job Details

Senior GPU Performance Engineer - CUDA

Introduction

In the realm of cutting-edge cryptography and decentralized applications, we're at the forefront, driven by a passionate mission to scale zero-knowledge proofs (ZKPs) for a decentralized future. With folding schemes, proof aggregation, and GPU acceleration, we're revolutionizing proof systems, promising enhanced security, privacy, and decentralization.

About the Company

Dedicated to empowering developers with robust infrastructure and user-friendly tools to build, deploy, and scale ZKP applications effectively. We are committed to pushing the scalability of proof systems to unprecedented levels.

About the Role

We are seeking a seasoned Senior GPU Performance Engineer to join our team and drive the advancement of ZKP acceleration. As a key member, you'll shape the future of modern cryptography by optimizing GPU-based solutions for ZKP applications. Your expertise in GPU computing, performance optimization, and parallel programming will redefine the capabilities of ZKPs, fostering a truly decentralized future.

What We Can Offer You

• Competitive base salary with founding member equity.
• Immersion in a team of top-notch global blockchain engineers.
• A flexible and innovative remote work environment.
• Room for continuous growth and development in the ZK field.

Key Responsibilities

• Design, develop, and optimize GPU-based algorithms and data structures to accelerate ZKP proof systems.
• Collaborate with the engineering team to identify performance bottlenecks and propose innovative solutions.
• Develop and maintain high-quality, well-documented code adhering to best practices for GPU programming.
• Analyze and optimize performance across a wide range of GPU architectures.
• Contribute to technical resources, including whitepapers and tutorials.
• Mentor junior engineers on GPU-related topics and performance optimization techniques.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field; Master's or PhD preferred.
• 2+ years of experience in GPU computing, with a focus on performance optimization and parallel programming.
• Proficiency in GPU programming languages such as CUDA.
• Strong understanding of computer architecture, memory systems, and parallel algorithms.
• Experience with profiling and debugging tools for GPU applications, such as NVIDIA Nsight.
• Familiarity with ZKP applications and blockchain technologies is a plus.
• Excellent problem-solving skills and ability to analyze complex systems.
• Strong communication skills and ability to work effectively in a collaborative team environment.
• Demonstrated passion for staying up-to-date with the latest advancements in GPU technology.